From e4e5a8668aac03753f0a970fb8b72f10dd028884 Mon Sep 17 00:00:00 2001 From: Quarto GHA Workflow Runner Date: Wed, 6 Dec 2023 17:52:47 +0000 Subject: [PATCH] Built site for gh-pages --- .nojekyll | 2 +- about.html | 13 +- blog.html | 49 +- blog/2017/call-to-join-forwards/index.html | 6 +- blog/2017/emily-robinson-interview/index.html | 6 +- .../index.html | 6 +- blog/2017/mapping-users/index.html | 6 +- blog/2017/r-in-africa/index.html | 6 +- .../index.html | 6 +- .../2017/users-relationship-with-r/index.html | 6 +- blog/2018/havanar/index.html | 6 +- blog/2018/r-in-latin-america/index.html | 6 +- .../index.html | 6 +- blog/2019/the-state-of-r-in-africa/index.html | 6 +- .../workshops-for-women-and-girls/index.html | 6 +- .../blacklivesmatter-statement/index.html | 6 +- .../southern-africa-project-2020/index.html | 6 +- .../package-development-modules/index.html | 6 +- community.html | 13 +- conferences.html | 13 +- contribution.html | 13 +- data.html | 19 +- docs/MCA_community_useR2016_survey/index.html | 19 +- .../index.html | 19 +- docs/index.html | 6 +- docs/nonresponse_useR2016_survey/index.html | 19 +- docs/recommendations_user/index.html | 13 +- edu/brisbane.html | 6 +- edu/chicago.html | 6 +- edu/index.html | 25 +- edu/nyc.html | 6 +- edu/workshops/index.html | 13 +- edu/york.html | 6 +- images/favicon.ico | Bin 0 -> 1835 bytes images/forwards.svg | 165 ++++ index.html | 19 +- listings.json | 20 +- logo-information.html | 13 +- package-dev.html | 615 ------------ privacy-policy.html | 13 +- search.json | 916 +++++++++--------- site_libs/bootstrap/bootstrap.min.css | 4 +- sitemap.xml | 136 ++- styles.css | 9 + 44 files changed, 1042 insertions(+), 1218 deletions(-) create mode 100644 images/favicon.ico create mode 100644 images/forwards.svg delete mode 100644 package-dev.html diff --git a/.nojekyll b/.nojekyll index 2469afa3..9c6d379a 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -e5654258 \ No newline at end of file +7f07dc04 \ No newline at end of file diff --git a/about.html b/about.html index 4d848de6..96b33b68 100644 --- a/about.html +++ b/about.html @@ -30,6 +30,7 @@ + @@ -61,9 +62,19 @@ "search-label": "Search" } } + + + + + + + + + + @@ -74,7 +85,7 @@
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Forwards diff --git a/edu/workshops/index.html b/edu/workshops/index.html index 68474609..b74939c5 100644 --- a/edu/workshops/index.html +++ b/edu/workshops/index.html @@ -30,6 +30,7 @@ + @@ -61,9 +62,19 @@ "search-label": "Search" } } + + + + + + + + + + @@ -74,7 +85,7 @@
Forwards diff --git a/edu/york.html b/edu/york.html index ad324d64..cab82a6c 100644 --- a/edu/york.html +++ b/edu/york.html @@ -30,6 +30,7 @@ + @@ -61,6 +62,9 @@ "search-label": "Search" } } + + + @@ -74,7 +78,7 @@
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Forwards diff --git a/listings.json b/listings.json index b9762a85..221dcea9 100644 --- a/listings.json +++ b/listings.json @@ -1,4 +1,14 @@ [ + { + "listing": "/edu/index.html", + "items": [ + "/blog/2017/girls-coding-workshop-melbourne/index.html", + "/blog/2018/havanar/index.html", + "/blog/2019/rladies-charlottesville-workshop-recap/index.html", + "/blog/2020/southern-africa-project-2020/index.html", + "/blog/2019/workshops-for-women-and-girls/index.html" + ] + }, { "listing": "/blog.html", "items": [ @@ -17,15 +27,5 @@ "/blog/2017/call-to-join-forwards/index.html", "/blog/2017/mapping-users/index.html" ] - }, - { - "listing": "/edu/index.html", - "items": [ - "/blog/2017/girls-coding-workshop-melbourne/index.html", - "/blog/2018/havanar/index.html", - "/blog/2019/rladies-charlottesville-workshop-recap/index.html", - "/blog/2020/southern-africa-project-2020/index.html", - "/blog/2019/workshops-for-women-and-girls/index.html" - ] } ] \ No newline at end of file diff --git a/logo-information.html b/logo-information.html index 808931fa..28df8568 100644 --- a/logo-information.html +++ b/logo-information.html @@ -30,6 +30,7 @@ + @@ -61,9 +62,19 @@ "search-label": "Search" } } + + + + + + + + + + @@ -74,7 +85,7 @@
Forwards diff --git a/package-dev.html b/package-dev.html deleted file mode 100644 index 00357b60..00000000 --- a/package-dev.html +++ /dev/null @@ -1,615 +0,0 @@ - - - - - - - - - -Forwards – package-dev - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Package Development Workshop for women and other underrepresented groups

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Location: University of York

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Forwards is the R Foundation taskforce on women and other under-represented groups and we are offering a free workshop designed for people who use R coding and want to learn more about creating impact from their code. It will cover package contribution and development thus addressing the skills gap that exists within the R and scientific coding community. For example, an analysis of CRAN package maintainers estimated that fewer than 15% were women, and a useR! participant survey found that women were less likely than men to have experience contributing to or writing packages. Whilst these data apply to women, underrepresented groups also include, but are not limited to, LGBTQ+ individuals, and people of colour.

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Workshop participants will learn to make code into an R package, do collaborative coding with GitHub, write a vignette or an article, build a package web page, and submit a package to CRAN. Participants can bring their own code that they wish to develop into a package or work with a provided example.

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Applications and Travel Scholarships

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Participation is free and there is a scholarship program for travel within the UK, child care and other reasonable costs arising from attending the workshop. Scholarships are funded by the R Consortium and a link to the scholarship application form is presented at the end of the workshop application process. In addition, members of the Biochemical Society can apply for a general travel grant to attend the workshop.

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Application form.

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The deadline for Scholarship applications is midnight 10 November 2019 with applicants being informed of the outcome on Friday 22 November. The deadline for workshop applications is midnight 1 January 2020.

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Code of Conduct

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Workshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.

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Full Day Package Development Workshop

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Workshop Slides

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0. Preliminaries

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1. Package orientation

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2. Package creation

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3. Git and GitHub

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4. Unit testing

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5. Package documentation

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6. Sharing

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Workshop Materials

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Demo package: sortnum

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© 2023 Forwards, under CC BY-NC 4.0 license.
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- - - - \ No newline at end of file diff --git a/privacy-policy.html b/privacy-policy.html index c7917c45..17e9fd81 100644 --- a/privacy-policy.html +++ b/privacy-policy.html @@ -30,6 +30,7 @@ + @@ -61,9 +62,19 @@ "search-label": "Search" } } + + + + + + + + + + @@ -74,7 +85,7 @@
Forwards diff --git a/search.json b/search.json index 597b1b1f..e6afa068 100644 --- a/search.json +++ b/search.json @@ -28,361 +28,319 @@ "text": "Data Security\nForwards will limit the data collected to that necessary for the task at hand. Since most surveys/forms will contain direct identifiers (e.g. name, email) and/or personal information (e.g. age, ethnicity, sexuality) we treat all data collected as confidential and take action to protect against breaches of personal identifiable information.\n\nData collection\nFor surveys conducted by Forwards or in partnership with collaborators, we ensure a secure survey/form platform is used. In particular, we ensure the platform is compliant with the General Data Protection Regulation (GDPR) of the European Union. Access to the platform is restricted to a small number of Forwards members and/or collaborators for the purpose of collecting and downloading the data. Once the full data is downloaded the copy on the survey/form platform is deleted.\n\n\nData storage\n\nSurveys\nRaw data containing personal and potentially identifiable information is stored in a private GitHub repository. Access to this repository is restricted to the survey team. If a member leaves the survey team, their access to the repository will be revoked and they will be asked to delete any personal copies of the data. Survey data may be shared with selected collaborators to assist us with statistical analysis, and potentially other academic researchers whose aims are consistent with our own, for example those studying participation in open source projects.\nAll collaborators are expected to observe good security practices, in particular:\n\nworking on password-protected computers that are screen-locked when unattended,\nensuring any back-ups are password-protected or encrypted,\nnot accessing private repositories over insecure WIFI connections, and\nnot working in an environment where third-parties can easily over-look.\n\n\n\nOther forms\nOther forms may be used to collect data for a specific purpose, e.g.  applications for a diversity scholarship scheme or expressions of interest in a conference buddy scheme. The data for these forms will either be stored in a private GitHub repository (or similarly secure online storage) or offline, with access restricted to the Forwards members responsible for the task.\n\n\n\nData retention\nRaw data is kept according to the following schedules:\n\n\n\n\n\n\n\nSurvey/form type\nRetention time\n\n\n\n\nDiversity scholarship applications\nUntil all scholarships paid out\n\n\nExpression of interest form\nUntil task/event completed\n\n\nDemographic/community survey\nIndefinitely\n\n\n\nData that has served its purpose will be deleted or anonymised - anonymised data may be kept to inform future activities.\n\n\nData publication\n\nSurveys\nSince survey data is of interest to the community at large, we do publish the results, but only in forms that minimise risk of personal identification and disclosure of sensitive information. This can mean presenting aggregate summaries (as for example in this Mapping useRs blog post), excluding certain variables, or modifying the data to achieve at least 3-anonymity over implicit identifiers (as for the useR2016 data published in the forwards package).\n\n\nOther forms\nData collected in other forms will not be published or shared with third parties.\n\n\n\nContact\nAny questions or comments on our privacy policy should be sent to rowforwards@gmail.com." }, { - "objectID": "logo-information.html", - "href": "logo-information.html", - "title": "Forwards logo information", - "section": "", - "text": "The Forwards logo is a derivative of the R logo, ©2016 The R Foundation, used under CC BY-SA 4.0." - }, - { - "objectID": "edu/york.html", - "href": "edu/york.html", - "title": "Forwards", - "section": "", - "text": "Forwards is the R Foundation taskforce on women and other under-represented groups and we are offering a free workshop designed for people who use R coding and want to learn more about creating impact from their code. It will cover package contribution and development thus addressing the skills gap that exists within the R and scientific coding community. For example, an analysis of CRAN package maintainers estimated that fewer than 15% were women, and a useR! participant survey found that women were less likely than men to have experience contributing to or writing packages. Whilst these data apply to women, underrepresented groups also include, but are not limited to, LGBTQ+ individuals, and people of colour.\nWorkshop participants will learn to make code into an R package, do collaborative coding with GitHub, write a vignette or an article, build a package web page, and submit a package to CRAN. Participants can bring their own code that they wish to develop into a package or work with a provided example.\n\n\n\nParticipation is free and there is a scholarship program for travel within the UK, child care and other reasonable costs arising from attending the workshop. Scholarships are funded by the R Consortium and a link to the scholarship application form is presented at the end of the workshop application process. In addition, members of the Biochemical Society can apply for a general travel grant to attend the workshop.\nApplication form.\nThe deadline for Scholarship applications is midnight 10 November 2019 with applicants being informed of the outcome on Friday 22 November. The deadline for workshop applications is midnight 1 January 2020.\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct." - }, - { - "objectID": "edu/york.html#package-development-workshop-for-women-and-other-underrepresented-groups", - "href": "edu/york.html#package-development-workshop-for-women-and-other-underrepresented-groups", - "title": "Forwards", - "section": "", - "text": "Forwards is the R Foundation taskforce on women and other under-represented groups and we are offering a free workshop designed for people who use R coding and want to learn more about creating impact from their code. It will cover package contribution and development thus addressing the skills gap that exists within the R and scientific coding community. For example, an analysis of CRAN package maintainers estimated that fewer than 15% were women, and a useR! participant survey found that women were less likely than men to have experience contributing to or writing packages. Whilst these data apply to women, underrepresented groups also include, but are not limited to, LGBTQ+ individuals, and people of colour.\nWorkshop participants will learn to make code into an R package, do collaborative coding with GitHub, write a vignette or an article, build a package web page, and submit a package to CRAN. Participants can bring their own code that they wish to develop into a package or work with a provided example.\n\n\n\nParticipation is free and there is a scholarship program for travel within the UK, child care and other reasonable costs arising from attending the workshop. Scholarships are funded by the R Consortium and a link to the scholarship application form is presented at the end of the workshop application process. In addition, members of the Biochemical Society can apply for a general travel grant to attend the workshop.\nApplication form.\nThe deadline for Scholarship applications is midnight 10 November 2019 with applicants being informed of the outcome on Friday 22 November. The deadline for workshop applications is midnight 1 January 2020.\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct." - }, - { - "objectID": "edu/nyc.html", - "href": "edu/nyc.html", + "objectID": "index.html", + "href": "index.html", "title": "Forwards", "section": "", - "text": "R Foundation taskforce on women and other under-represented groups\n\n\n\nAT&T NYC Data Science Research Center\n33 Thomas Street, 1st Floor\nNew York, NY 10007\n\n\n\n\n\nThis workshop is open to high school girls in grades 11 and 12 who are interested in STEM, coding, and data analysis. No prior coding experience required. Applicants will be notified of acceptance status by early/mid October.\nAPPLY NOW!\n\n\n\nHave you ever wondered how data scientists formulate questions, analyze and visualize data, and draw conclusions? In this workshop for NYC high school girls interested in STEM, coding, and data analysis, students will be introduced to coding in R through an investigation of NYC transportation data: Citibike, Taxi, and Flights. Participants will receive a certificate of completion at the end of the workshop.\n\n\n\nTransportation data is rich with potential insights into how people move around NYC.\n\n\n\n Source\n\n\n Source\n\n\n Source\n\n\n\n\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Students are responsible for their own transportation to and from the workshop, however each participant will be provided with a 2-trip MetroCard to reimburse the cost of travel. Lunch will be provided.\n\n\n\nEmily Dodwell: Emily Dodwell is a Senior Inventive Scientist in the Statistics Research Department at AT&T Labs and a member of the R Forwards teaching team. Prior to joining AT&T Labs in 2015, Emily taught high school math for three years at Choate Rosemary Hall. She received her M.A. in statistics from Yale University and B.A. in mathematics from Smith College.\nJoyce Robbins: Joyce Robbins, Ph.D., is Lecturer in Discipline in the Statistics Department at Columbia University, where she specializes in data visualization. She is a member of the R Forwards teaching team, and she was elected to serve as publications officer of the Statistical Graphics Section of the American Statistical Association Section beginning in 2018. Robbins received her doctorate in sociology from Columbia University, her M.A. in sociology and anthropology from Tel Aviv University and her B.S.E. in civil engineering and operations research from Princeton University.\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email rowforwards@gmail.com with any questions, and see here for more information about this workshop series.\nAPPLY NOW!\nWorkshop flyer PDF" + "text": "Leading the R community forwards in widening the participation of women and other under-represented groups.\nFind out more about the task force." }, { - "objectID": "edu/nyc.html#data-science-in-r-nyc-coding-workshop-for-high-school-girls-11th-and-12th-grades", - "href": "edu/nyc.html#data-science-in-r-nyc-coding-workshop-for-high-school-girls-11th-and-12th-grades", + "objectID": "index.html#mission", + "href": "index.html#mission", "title": "Forwards", "section": "", - "text": "R Foundation taskforce on women and other under-represented groups\n\n\n\nAT&T NYC Data Science Research Center\n33 Thomas Street, 1st Floor\nNew York, NY 10007\n\n\n\n\n\nThis workshop is open to high school girls in grades 11 and 12 who are interested in STEM, coding, and data analysis. No prior coding experience required. Applicants will be notified of acceptance status by early/mid October.\nAPPLY NOW!\n\n\n\nHave you ever wondered how data scientists formulate questions, analyze and visualize data, and draw conclusions? In this workshop for NYC high school girls interested in STEM, coding, and data analysis, students will be introduced to coding in R through an investigation of NYC transportation data: Citibike, Taxi, and Flights. Participants will receive a certificate of completion at the end of the workshop.\n\n\n\nTransportation data is rich with potential insights into how people move around NYC.\n\n\n\n Source\n\n\n Source\n\n\n Source\n\n\n\n\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Students are responsible for their own transportation to and from the workshop, however each participant will be provided with a 2-trip MetroCard to reimburse the cost of travel. Lunch will be provided.\n\n\n\nEmily Dodwell: Emily Dodwell is a Senior Inventive Scientist in the Statistics Research Department at AT&T Labs and a member of the R Forwards teaching team. Prior to joining AT&T Labs in 2015, Emily taught high school math for three years at Choate Rosemary Hall. She received her M.A. in statistics from Yale University and B.A. in mathematics from Smith College.\nJoyce Robbins: Joyce Robbins, Ph.D., is Lecturer in Discipline in the Statistics Department at Columbia University, where she specializes in data visualization. She is a member of the R Forwards teaching team, and she was elected to serve as publications officer of the Statistical Graphics Section of the American Statistical Association Section beginning in 2018. Robbins received her doctorate in sociology from Columbia University, her M.A. in sociology and anthropology from Tel Aviv University and her B.S.E. in civil engineering and operations research from Princeton University.\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email rowforwards@gmail.com with any questions, and see here for more information about this workshop series.\nAPPLY NOW!\nWorkshop flyer PDF" + "text": "Leading the R community forwards in widening the participation of women and other under-represented groups.\nFind out more about the task force." }, { - "objectID": "edu/chicago.html", - "href": "edu/chicago.html", + "objectID": "index.html#news", + "href": "index.html#news", "title": "Forwards", - "section": "", - "text": "Materials for this workshop, including slides and sample code, can be found at this Github repository.\n\n\n\nCenter for Spatial Data Science\n5735 S Ellis Ave, 2nd Floor\nChicago, Illinois 60637\n\n\n\n\n\nApplications are available at this Google Form. We encourage you to apply, especially if you’ve never developed a package before. We’ll walk you through the basics, and you’ll leave having put together your first R package. Applications for out-of-town attendees will close on January 15, 2019, while applications for attendees based in Chicago will close on February 2, 2019.\nApply now!\n\n\n\nCurious about package development, but not sure where to start? This workshop is for you! Run by R-Ladies Chicago, the goal of this workshop is to empower you to start contributing back to the R ecosystem with package development. We’ll be using materials developed by Hadley Wickham, Jenny Bryan, and Di Cook for the Forwards teaching team.\nBy the end of this day-long workshop, you should know how to:\n\nmake your code into an R package,\ndo collaborative coding with GitHub,\nwrite a vignette or an article,\nbuild a web page for your package, and\nsubmit a package to CRAN.\n\nBring your own code that you want to make into a package, or work with our example.\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Breakfast and lunch will be provided.\nWe may be able to provided limited travel grants to out-of-town attendees, so please indicate on the application if you need support. Additionally, please let us know on the application if you will need childcare.\n\n\n\nStephanie Kirmer and Angela Li of R-Ladies Chicago co-taught the workshop. Stephanie is a Senior Data Scientist at Uptake and Angela is the R Spatial Advocate at the Center for Spatial Data Science.\nOur helpers were Katherine Simeon, Ola Giwa, and Nicole Burke from R-Ladies Chicago - thank you for your time!\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email angela [at] rladies.org with any questions, and see the main Education page for more information about Forwards teaching initiatives." + "section": "News", + "text": "News\nFor more details on past workshops, see the Edu section.\n2019/05/25 First ever R conference in East Africa: SatRdays Kampala 2019 Lend your support to this pathbreaking conference by contributing to SatRdays Kampala’s Indiegogo campaign\n\n2019-04-06, Dublin Isabella Gollini, with Bruna Wundervald, Chiara Cotroneo, and Jo Niec, teach “Develop Packages in R”\n2019-03-30, Brisbane Di Cook and a team of brilliant women teach “R Coding Workshop for Year 11 Girls”\n2019-02-23, Chicago Stephanie Kirmer and Angela Li teach “Women’s Package Development Workshop”, jointed hosted with R-Ladies Chicago\n2018-10-27, New York City Emily Dodwell and Joyce Robbins lead “Data Science in R: Coding Workshop for 11th and 12th Grade Girls”\n2018-07-30, Vancouver Di Cook serves as panelist on late breaking session at JSM2018, Addressing Sexual Misconduct in the Statistics Community Organizer blog post\n2018-06-23, Cardiff, Wales Heather Turner teaches “Upgrade Your Workflow with a Custom Package” at Cardiff satRday\n2018-05-24, Melbourne Earo Wang leads “Package Development Workshop for Women: Everything you need to know to create your own R package” at R Ladies Melbourne slides, code\n2018-05-14, Budapest Package Development Workshop for Women at eRum 2018\nolder news items" }, { - "objectID": "edu/chicago.html#womens-package-development-workshop-by-r-ladies-chicago-and-forwards", - "href": "edu/chicago.html#womens-package-development-workshop-by-r-ladies-chicago-and-forwards", + "objectID": "index.html#mastodon-posts", + "href": "index.html#mastodon-posts", "title": "Forwards", - "section": "", - "text": "Materials for this workshop, including slides and sample code, can be found at this Github repository.\n\n\n\nCenter for Spatial Data Science\n5735 S Ellis Ave, 2nd Floor\nChicago, Illinois 60637\n\n\n\n\n\nApplications are available at this Google Form. We encourage you to apply, especially if you’ve never developed a package before. We’ll walk you through the basics, and you’ll leave having put together your first R package. Applications for out-of-town attendees will close on January 15, 2019, while applications for attendees based in Chicago will close on February 2, 2019.\nApply now!\n\n\n\nCurious about package development, but not sure where to start? This workshop is for you! Run by R-Ladies Chicago, the goal of this workshop is to empower you to start contributing back to the R ecosystem with package development. We’ll be using materials developed by Hadley Wickham, Jenny Bryan, and Di Cook for the Forwards teaching team.\nBy the end of this day-long workshop, you should know how to:\n\nmake your code into an R package,\ndo collaborative coding with GitHub,\nwrite a vignette or an article,\nbuild a web page for your package, and\nsubmit a package to CRAN.\n\nBring your own code that you want to make into a package, or work with our example.\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Breakfast and lunch will be provided.\nWe may be able to provided limited travel grants to out-of-town attendees, so please indicate on the application if you need support. Additionally, please let us know on the application if you will need childcare.\n\n\n\nStephanie Kirmer and Angela Li of R-Ladies Chicago co-taught the workshop. Stephanie is a Senior Data Scientist at Uptake and Angela is the R Spatial Advocate at the Center for Spatial Data Science.\nOur helpers were Katherine Simeon, Ola Giwa, and Nicole Burke from R-Ladies Chicago - thank you for your time!\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email angela [at] rladies.org with any questions, and see the main Education page for more information about Forwards teaching initiatives." + "section": "Mastodon posts", + "text": "Mastodon posts\n\n\n\n\n\n<div class=\"loading-spinner\"></div>" }, { - "objectID": "docs/recommendations_user/index.html", - "href": "docs/recommendations_user/index.html", - "title": "Recommendations to increase the Participation of Women at useR! Conferences", + "objectID": "edu/workshops/index.html", + "href": "edu/workshops/index.html", + "title": "Workshops for Women and Girls", "section": "", - "text": "The following recommendations are made for future useR! conferences, as achievable actions to promote the inclusion of women.\n\n\nSince 2014, 2/6 invited speakers have been women. Although a 50:50 gender split is something to strive for, we are aware that this would be a big jump and the focus should be on sustaining the current level in the medium term. The step up in 2014 has already helped to raise the profile of women in the R community.\n\n\n\nWe recommend that the program committee is selected to be approximately 50:50 men and women. Women have in fact been well-represented in the past, e.g. useR! 2015 had 4/11 women and useR! 2016 has 7/13 women. Being on the program committee is a boost to the women selected: recognising their expertise, providing experience for their CV, raising their profile in the R community and potentially reducing the cost of their attendance.\n\n\n\nSimilarly we recommend that 50% of the sessions are chaired by women, ideally with women making up 50% of the session chairs (often people chair multiple sessions). Since the program committee are often called upon to chair sessions, this should follow to some degree from the previous recommendation. However it is also an opportunity to increase the involvement of women on the edges of the R community, e.g. local women who have not previously had much involvement in useR!, regular attendees who have previously not had a formal role, women working in business/industry who are often not considered for such roles, etc.\n\n\n\nNot all useR! conferences have panel discussions, but with the exception of the heR panel (“Why aren’t more women R users?”) at useR! 2014, women have barely been represented. We recommend that any panels should reflect the composition of recent useR!s, i.e. at least 20% should be women.\n\n\n\nTo demonstrate the commitment of the R community to promoting the inclusion of women, we recommend publishing recent statistics of gender balance on the conference website. A good example is set here http://www.lorneproteins.org/policies/. We plan to collate such statistics on the Task Force webpage (https://forwards.github.io/), so that such tables could easily be produced for future useR!s." + "text": "Overview\nThanks to generous funding from the R Consortium, Forwards is pleased to offer the following workshops to support the development of coding skills and increase the participation of women in the R community:\n\nWorkshops for women are designed for women with some R coding experience who wish to learn more about package development, thereby addressing the skills gap that exists within the R community. As of 2016, an analysis of CRAN package maintainers estimated that fewer than 15% were women, and a useR! participant survey found that women were less likely than men to have experience contributing to or writing packages. Workshop participants learn to make code into an R package, do collaborative coding with GitHub, write a vignette or an article, build a package web page, and submit a package to CRAN. Participants can bring their own code that they wish to develop into a package or work with a Forwards example.\nWorkshops for high school girls serve as an introduction to coding in R and are designed for students interested in STEM, coding, and data analysis. Participants learn about plotting data, web scraping, and the development of Shiny apps. A selection of topics related to contemporary current affairs are used, and where possible, incorporate data specific to the workshop’s geographic location.\n\n\n\nUpcoming workshops\n\nPackage development workshop for women & other underrepresented groups at the University York\n2020-01-07, York, UK\nFree to attend, travel scholarships available for travel within the UK. More details.\nInstructors: Emma Rand, Susannah Cowtan\n\n\n\nPast Workshops\n\nForwards and ACEMS R Coding Workshop for Year 11 Girls at River City Labs\n2019-03-30, Brisbane, Australia\nFree to attend, More details\nInstructors: Di Cook and a team of brilliant young women\nDevelop Packages in R at UCD O’Brien Centre for Science\n2019-04-06, Dublin, Ireland\nThere is a small charge of EUR 5.85 to cover training materials, however tea/coffee and lunch are provided.\nBook your ticket\nInstructors: Isabella Gollini, assisted by Bruna Wundervald, Chiara Cotroneo, and Jo Niec.\nWomen’s Package Development Workshop jointed hosted with R-Ladies Chicago\n2019-02-23 Chicago, USA\nInstructor: Stephanie Kirmer and Angela Li\nData Science in R: Coding Workshop for 11th and 12th Grade Girls at AT&T NYC Data Science Research Center\n2018-10-27 New York City, USA\nInstructors: Emily Dodwell and Joyce Robbins\nUpgrade Your Workflow with a Custom Package at Cardiff satRday\n2018-06-23 Cardiff, Wales, United Kingdom\nInstructor: Heather Turner\nPackage Development Workshop for Women: Everything you need to know to create your own R package at R Ladies Melbourne by Earo Wang, slides, code 2018-05-24 Melbourne, Australia\nPackage Development Workshop for Women at eRum 2018\n2018-05-14 Budapest, Hungary\nInstructors: Heather Turner and Isabella Gollini\nCoding Workshop for 12th Grade Girls at The University of Auckland\n2017-12-08 Auckland, New Zealand\nInstructor: Di Cook\nWomen’s Coding Workshop at The University of Auckland\n2017-12-07 Auckland, New Zealand\nInstructors: Jenny Bryan, Di Cook, and Hadley Wickham\nCoding Workshop for 11th Grade Girls at Kathleen Syme Library\n2017-10-28 Melbourne, Australia\nInstructor: Di Cook\n\n\n\nCode of Conduct\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\nComputing Information\nIf possible, please install the most recent versions of the following software on your laptop prior to the workshop:\n\nR 3.5.1 “Feather Spray” (release date 2018-07-02)\nRStudio Desktop 1.1.456 (release date 2018-07-19)\n\nIf you have trouble, there will be technical support prior to the start of the workshop (arrive 30 minutes early).\n\n\nWorkshop Materials\nWorkshop materials are available on GitHub under a CC-BY-NC 3.0 license." }, { - "objectID": "docs/recommendations_user/index.html#recommendations", - "href": "docs/recommendations_user/index.html#recommendations", - "title": "Recommendations to increase the Participation of Women at useR! Conferences", + "objectID": "edu/index.html", + "href": "edu/index.html", + "title": "Education", "section": "", - "text": "The following recommendations are made for future useR! conferences, as achievable actions to promote the inclusion of women.\n\n\nSince 2014, 2/6 invited speakers have been women. Although a 50:50 gender split is something to strive for, we are aware that this would be a big jump and the focus should be on sustaining the current level in the medium term. The step up in 2014 has already helped to raise the profile of women in the R community.\n\n\n\nWe recommend that the program committee is selected to be approximately 50:50 men and women. Women have in fact been well-represented in the past, e.g. useR! 2015 had 4/11 women and useR! 2016 has 7/13 women. Being on the program committee is a boost to the women selected: recognising their expertise, providing experience for their CV, raising their profile in the R community and potentially reducing the cost of their attendance.\n\n\n\nSimilarly we recommend that 50% of the sessions are chaired by women, ideally with women making up 50% of the session chairs (often people chair multiple sessions). Since the program committee are often called upon to chair sessions, this should follow to some degree from the previous recommendation. However it is also an opportunity to increase the involvement of women on the edges of the R community, e.g. local women who have not previously had much involvement in useR!, regular attendees who have previously not had a formal role, women working in business/industry who are often not considered for such roles, etc.\n\n\n\nNot all useR! conferences have panel discussions, but with the exception of the heR panel (“Why aren’t more women R users?”) at useR! 2014, women have barely been represented. We recommend that any panels should reflect the composition of recent useR!s, i.e. at least 20% should be women.\n\n\n\nTo demonstrate the commitment of the R community to promoting the inclusion of women, we recommend publishing recent statistics of gender balance on the conference website. A good example is set here http://www.lorneproteins.org/policies/. We plan to collate such statistics on the Task Force webpage (https://forwards.github.io/), so that such tables could easily be produced for future useR!s." - }, - { - "objectID": "docs/recommendations_user/index.html#other-issues-to-consider", - "href": "docs/recommendations_user/index.html#other-issues-to-consider", - "title": "Recommendations to increase the Participation of Women at useR! Conferences", - "section": "Other Issues to Consider", - "text": "Other Issues to Consider\nThe following sections outline some other issues that we recommend organisers of useR! consider to encourage the participation of women.\n\nTutorials\nWe have not evaluated the proportion of women tutors at useR! conferences over the years, but note that 6/18 tutorials are being presented by women at useR! 2016. This is in line with the proportion of invited speakers, so seems a reasonable proportion to aim for. This may be hard to put into practice as tutorials are generally contributed rather than invited, however gender balance might be taken into account when ranking submissions or making a final selection.\n\n\nQuotas\nA large proportion of abstracts contributed to useR! are accepted in some form and there is no evidence of gender bias in the rejections or the assigned presentation format. Quotas might be considered in particular cases to encourage the participation of women. Lightning talks may be particularly suitable for this as the number of abstracts is often much greater than the number of slots. The following links provide good arguments for using quotas: http://womeninscienceaust.org/2015/11/15/achieving-gender-balance-in-less-than-3-years/; http://curt-rice.com/2014/07/03/2-ways-quotas-for-women-raise-quality/. Scope for using quotas may be limited by the gender balance in submitted abstracts: 50:50 may simply not be possible. Alternative actions to encourage the contribution of women might still be considered, e.g. favouring women presenters when ranking borderline abstracts.\n\n\nOutreach to Women\nEfforts should be made to attract women to the conference. An example from useR! 2016 was to email prominent female R users inviting them to the conference and asking them to encourage their colleagues/students, particularly women, to participate. Another idea might be to provide a template email at the end of the registration form to invite a colleague or friend to useR!, with an encouragement to reach out to potential female participants.\n\n\nLocal Groups\nIf there are local coding groups for women, it is worth considering whether these groups can be involved in any way. There might be a student society for women in computer science or an R-ladies group, for example.\n\n\nScholarships/Funding\nFunding obviously plays a large part in the ability of women to attend useR!. useR! 2016 is offering scholarships aimed at young researchers (funded by the American Statistical Association) and diversity scholarships aimed at minority groups such as LGBT people or people with disabilities, as well as women. Links to any external funding sources might be added to the conference website.\n\n\nChildcare/Family-friendliness\nThe family-friendliness of the conference should also be considered:\n\nIs childcare available on campus/at any of the hotels? Such information would be useful to put on the website.\nCould any sponsorship money be allocated to assistance with childcare?\nIs there any potential for a “family room” suitable for participants to take children where (the main) talks could be streamed?\nAre children welcome in sessions?" - }, - { - "objectID": "docs/recommendations_user/index.html#reporting-back", - "href": "docs/recommendations_user/index.html#reporting-back", - "title": "Recommendations to increase the Participation of Women at useR! Conferences", - "section": "Reporting Back", - "text": "Reporting Back\nWe hope that following the recommendations and considering the issues above will help to increase the participation of women in useR! conferences. To assist with this endeavour, conference organisers should share the outcomes of any initiatives to increase diversity. In particular, the gender of participants should be recorded to monitor the gender balance of attendees, invited speakers, presenters of contributed presentations/tutorials (broken down by presentation format), session chairs, and members of the local and program committees." + "text": "The Forwards teaching team support the work of the taskforce via the following projects:" }, { - "objectID": "docs/index.html", - "href": "docs/index.html", - "title": "Reports", - "section": "", - "text": "2017-06-18: useR! 2016 participants and the R community: a multivariate analysis\n2017-06-17: useR! 2016 participants and R programming: a multivariate analysis\n2016-10-07: Non-response in useR! 2016 Survey\n\n\n\n2016-04-09: Recommendations to increase the Participation of Women at useR! Conferences" + "objectID": "edu/index.html#education-blog-posts", + "href": "edu/index.html#education-blog-posts", + "title": "Education", + "section": "Education blog posts", + "text": "Education blog posts\n\n\n \n \n \n Order By\n Default\n \n Title\n \n \n Date - Oldest\n \n \n Date - Newest\n \n \n Author\n \n \n \n \n \n \n \n\n\n\n\n \n\n\n\n\nGirls Coding Workshop, Melbourne\n\n\n\n\n\nGirls Coding Workshop, Melbourne\n\n\n\n\n\n\nNov 20, 2017\n\n\nDi Cook\n\n\n\n\n\n\n \n\n\n\n\nHavanaR Workshop 2018\n\n\n\n\n\nAnnouncement of joint >eR-Biostat and Forwards workshop in Havana, on visualisation methods and exploratory analysis of high dimensional and multivariate datasets in R.\n\n\n\n\n\n\nJul 7, 2018\n\n\nZiv Shkedy, Julie Josse\n\n\n\n\n\n\n \n\n\n\n\nRecap of R-Ladies Charlottesville Forwards Workshop\n\n\n\n\n\nLessons from R-Ladies Charlottesville Forwards Workshop\n\n\n\n\n\n\nNov 22, 2019\n\n\nAngela Li, Samantha Toet\n\n\n\n\n\n\n \n\n\n\n\nSouthern Africa Project 2020\n\n\n\n\n\nReview of the R training and community events organized as part of the Forwards Southern Africa Project 2020, in South Africa, Eswatini and Botswana.\n\n\n\n\n\n\nMay 25, 2020\n\n\nHeather Turner\n\n\n\n\n\n\n \n\n\n\n\nWorkshops for Women and Girls\n\n\n\n\n\nRound up of Forwards workshops supported by a grant from the R Consortium, to develop R package development skills among women and R coding skills among high school girls.\n\n\n\n\n\n\nSep 22, 2019\n\n\nForwards Teaching Team\n\n\n\n\n\n\nNo matching items" }, { - "objectID": "docs/index.html#survey-reports", - "href": "docs/index.html#survey-reports", - "title": "Reports", + "objectID": "edu/brisbane.html", + "href": "edu/brisbane.html", + "title": "Forwards", "section": "", - "text": "2017-06-18: useR! 2016 participants and the R community: a multivariate analysis\n2017-06-17: useR! 2016 participants and R programming: a multivariate analysis\n2016-10-07: Non-response in useR! 2016 Survey" + "text": "R Foundation taskforce on women and other under-represented groups\n\n\n\nRiver City Labs\n\n\n\n\n\nThis workshop is open to high school girls in year 11 who are interested in STEM, coding, and data analysis. No prior coding experience required.\nAPPLY NOW!\n\n\n\nHave you ever wondered how data scientists formulate questions, analyze and visualize data, and draw conclusions? In this workshop for Brisbane high school girls interested in STEM, coding, and data analysis, students will be introduced to coding in R through an investigation of Atlas of Living Australia data, looking at what wildlife lives around Brisbane. Participants will receive a certificate of completion at the end of the workshop.\n\n\n\n\n Data source: OECD PISA\n\n\n Brush turkeys in Brisbane\n\n\n Data source: ALA\n\n\n\n\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Students are responsible for their own transportation to and from the workshop. Morning, afternoon tea and lunch will be provided.\n\n\n\nDi Cook: Di Cook is a professor of business analytics at Monash University. She has a B.Sc/Di.Ed in Mathematics and Statistics from University of New England, and MSc/PhD in Statistics from Rutgers University in the USA. Prior to joining Monash in 2015, she spent 20 years teaching data science at Iowa State University. Di is a member of the R foRwards taskforce, a member of the R Foundation, elected Fellow of the American Statistical Association, past editor for the Journal of Computational and Graphical Statistics, and current chair of the American Statistical Association section on Statistical Graphics.\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email rowforwards@gmail.com with any questions, and see here for more information about this workshop series.\nAPPLY NOW!\nWorkshop flyer PDF" }, { - "objectID": "docs/index.html#recommendations-to-the-r-foundation", - "href": "docs/index.html#recommendations-to-the-r-foundation", - "title": "Reports", + "objectID": "edu/brisbane.html#acems-and-forwards-r-coding-workshop-for-high-school-girls", + "href": "edu/brisbane.html#acems-and-forwards-r-coding-workshop-for-high-school-girls", + "title": "Forwards", "section": "", - "text": "2016-04-09: Recommendations to increase the Participation of Women at useR! Conferences" + "text": "R Foundation taskforce on women and other under-represented groups\n\n\n\nRiver City Labs\n\n\n\n\n\nThis workshop is open to high school girls in year 11 who are interested in STEM, coding, and data analysis. No prior coding experience required.\nAPPLY NOW!\n\n\n\nHave you ever wondered how data scientists formulate questions, analyze and visualize data, and draw conclusions? In this workshop for Brisbane high school girls interested in STEM, coding, and data analysis, students will be introduced to coding in R through an investigation of Atlas of Living Australia data, looking at what wildlife lives around Brisbane. Participants will receive a certificate of completion at the end of the workshop.\n\n\n\n\n Data source: OECD PISA\n\n\n Brush turkeys in Brisbane\n\n\n Data source: ALA\n\n\n\n\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Students are responsible for their own transportation to and from the workshop. Morning, afternoon tea and lunch will be provided.\n\n\n\nDi Cook: Di Cook is a professor of business analytics at Monash University. She has a B.Sc/Di.Ed in Mathematics and Statistics from University of New England, and MSc/PhD in Statistics from Rutgers University in the USA. Prior to joining Monash in 2015, she spent 20 years teaching data science at Iowa State University. Di is a member of the R foRwards taskforce, a member of the R Foundation, elected Fellow of the American Statistical Association, past editor for the Journal of Computational and Graphical Statistics, and current chair of the American Statistical Association section on Statistical Graphics.\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email rowforwards@gmail.com with any questions, and see here for more information about this workshop series.\nAPPLY NOW!\nWorkshop flyer PDF" }, { - "objectID": "docs/MCA_community_useR2016_survey/index.html", - "href": "docs/MCA_community_useR2016_survey/index.html", - "title": "useR! 2016 participants and the R community: a multivariate analysis", + "objectID": "docs/nonresponse_useR2016_survey/index.html", + "href": "docs/nonresponse_useR2016_survey/index.html", + "title": "Non-response in useR! 2016 Survey", "section": "", - "text": "The useR! survey gathers responses to questions on different themes for 455 attendees: demographic characteristics, R programming and involvement in the R community. The separate analyses of each question in each theme are detailed in the posts Mapping useRs, useRs Relationship with R and Community Involvement of useRs. A multivariate analysis of the R programming questions is detailed in a companion report. Here, we perform MCA on the R community questions.\n\n\n\nQuestions are the following ones:\n\nQ18 Do you consider yourself part of the R community?\nQ19 Which of the following resources do you use for support? Select all that apply\n\nQ19_A The R mailing lists\nQ19_B The #rstats hashtag on Twitter\nQ19_C The R StackOverflow queues\nQ19_D The R IRC channel\nQ19_E The rOpenSci mailing lists or chat forums\nQ19_F The Bioconductor support site\nQ19_H Other\n\nQ20 What would be your preferred medium for R community news (e.g. events, webinars, opportunities)?\nQ21 Do you attend R user group meetings in your local area?\nQ22 If you do: you do: what type of user group is it?\nQ23 If you do not: why not?\nQ24 Which of the following would make you more likely to participate in the R community, or improve your experience? Tick any that apply.\n\nQ24_A New R user group near me (specify location in comments box)\nQ24_B New R user group near me aimed at my demographic (specify relevant group in comments box)\nQ24_C Free local introductory R workshops\nQ24_D Paid local advanced R workshops\nQ24_E R workshop at conference in my domain (specify domain/conference in comments box)\nQ24_F R workshop aimed at my demographic (specify relevant group in comments box)\nQ24_G Mentoring (e.g. first CRAN submission/useR! abstract submission/GitHub contribution)\nQ24_H Training in non-English language (specify language in comments box)\nQ24_I Training that accommodates my disability (specify disability in comments box)\nQ24_J Online forum to discuss R-related issues\nQ24_K Online support group for my demographic (specify relevant group in comments box)\nQ24_L Special facilities at R conferences (give further detail in comments box)\nQ24_M Comments on answers above\n\nQ25 What other ideas do you have for improving the R community?\nQ26 Do you have any feedback for the survey authors?\n\n\n\n\n\nQuestion Q20 has a category “others” which corresponds to free text answers. We add new categories for this variable by grouping common answers and we name the new variables with the suffix “_new’’. For instance, there is a variable Q20_new with a new category medium_R-bloggers.\nQuestion Q19_H also corresponds to free text answers. It has been recoded with Q19_H_new to Q19_N_new by grouping common answers: for instance, Q19_K_new has two categories Github_yes or Github_no.\nQ21, Q22 and Q23 have been merged in a variable Q21_new since Q22 and Q23 are filled-in depending on the answer on Q21. For example, for Q21 Do you attend R user group meetings in your local area?, if the respondent answers no, they answer Q23 If you do not: why not?, with I am too busy. This is coded in the variable Q21_new, with the category meeting_no_I am too busy.\nQ24_M, Q25 and Q26 are not analysed.\nNon-respondents identified in the MCA Rprogramming document are also excluded since they do not answer to R community questions as well.\nCategories are renamed to be easily understandable. In particular, the two categories for answers completed by checking a box are recoded as yes, if the box is checked, or recoded as no otherwise." + "text": "The useR! survey received a total of 455 responses out of 904 attendees. Anticipating a high proportion of non-response, questions were included in the survey on participants’ gender, registration type and country of residence, with a view to adjusting observed counts in each cross-classified group to match the proportions in the total useR! 2016 population. Unfortunately the country of residence was not recorded during registration and could not be reliably derived from available information such as affiliation. Although registration type should have been available, in practice it was missing for about one third of participants. This leaves gender, which was (self-)recorded for presenters, but not for other attendees. In order to obtain a gender assignment for all participants, the first names were analysed with the genderizer package, which predicts gender from first name, based on profiles scraped from the web. For participants where the gender was unknown, the genderizer prediction was used if it was based on a sample > 10 and had probability > 0.9, otherwise the gender was assigned based on a manual web search, where this led to a clear assignment. This gave estimates of 235 female, 593 male and 76 undetermined.\nAssuming that the gender distribution is similar in the undetermined group, the survey population overrepresents female attendees by about 10%:\n\n\n\nGender\nSurvey Percentage\nAttendee Percentage\n\n\n\n\nFemale\n37.31\n28.38\n\n\nMale\n62.47\n71.62\n\n\nNon-Binary\n0.22\nNA\n\n\n\n(The assumption that the undetermined have a similar gender distribution seems reasonable, as similar estimates of attendee breakdown were obtained based on genderizer results only, where there were 52.17% undetermined). This over-representation of females is a common phenomenon in surveys and particularly unsurprising here as females may be more motivated to respond to a survey run by the Women in R taskforce." }, { - "objectID": "docs/MCA_community_useR2016_survey/index.html#introduction", - "href": "docs/MCA_community_useR2016_survey/index.html#introduction", - "title": "useR! 2016 participants and the R community: a multivariate analysis", + "objectID": "docs/nonresponse_useR2016_survey/index.html#background", + "href": "docs/nonresponse_useR2016_survey/index.html#background", + "title": "Non-response in useR! 2016 Survey", "section": "", - "text": "The useR! survey gathers responses to questions on different themes for 455 attendees: demographic characteristics, R programming and involvement in the R community. The separate analyses of each question in each theme are detailed in the posts Mapping useRs, useRs Relationship with R and Community Involvement of useRs. A multivariate analysis of the R programming questions is detailed in a companion report. Here, we perform MCA on the R community questions.\n\n\n\nQuestions are the following ones:\n\nQ18 Do you consider yourself part of the R community?\nQ19 Which of the following resources do you use for support? Select all that apply\n\nQ19_A The R mailing lists\nQ19_B The #rstats hashtag on Twitter\nQ19_C The R StackOverflow queues\nQ19_D The R IRC channel\nQ19_E The rOpenSci mailing lists or chat forums\nQ19_F The Bioconductor support site\nQ19_H Other\n\nQ20 What would be your preferred medium for R community news (e.g. events, webinars, opportunities)?\nQ21 Do you attend R user group meetings in your local area?\nQ22 If you do: you do: what type of user group is it?\nQ23 If you do not: why not?\nQ24 Which of the following would make you more likely to participate in the R community, or improve your experience? Tick any that apply.\n\nQ24_A New R user group near me (specify location in comments box)\nQ24_B New R user group near me aimed at my demographic (specify relevant group in comments box)\nQ24_C Free local introductory R workshops\nQ24_D Paid local advanced R workshops\nQ24_E R workshop at conference in my domain (specify domain/conference in comments box)\nQ24_F R workshop aimed at my demographic (specify relevant group in comments box)\nQ24_G Mentoring (e.g. first CRAN submission/useR! abstract submission/GitHub contribution)\nQ24_H Training in non-English language (specify language in comments box)\nQ24_I Training that accommodates my disability (specify disability in comments box)\nQ24_J Online forum to discuss R-related issues\nQ24_K Online support group for my demographic (specify relevant group in comments box)\nQ24_L Special facilities at R conferences (give further detail in comments box)\nQ24_M Comments on answers above\n\nQ25 What other ideas do you have for improving the R community?\nQ26 Do you have any feedback for the survey authors?\n\n\n\n\n\nQuestion Q20 has a category “others” which corresponds to free text answers. We add new categories for this variable by grouping common answers and we name the new variables with the suffix “_new’’. For instance, there is a variable Q20_new with a new category medium_R-bloggers.\nQuestion Q19_H also corresponds to free text answers. It has been recoded with Q19_H_new to Q19_N_new by grouping common answers: for instance, Q19_K_new has two categories Github_yes or Github_no.\nQ21, Q22 and Q23 have been merged in a variable Q21_new since Q22 and Q23 are filled-in depending on the answer on Q21. For example, for Q21 Do you attend R user group meetings in your local area?, if the respondent answers no, they answer Q23 If you do not: why not?, with I am too busy. This is coded in the variable Q21_new, with the category meeting_no_I am too busy.\nQ24_M, Q25 and Q26 are not analysed.\nNon-respondents identified in the MCA Rprogramming document are also excluded since they do not answer to R community questions as well.\nCategories are renamed to be easily understandable. In particular, the two categories for answers completed by checking a box are recoded as yes, if the box is checked, or recoded as no otherwise." - }, - { - "objectID": "docs/MCA_community_useR2016_survey/index.html#analysis", - "href": "docs/MCA_community_useR2016_survey/index.html#analysis", - "title": "useR! 2016 participants and the R community: a multivariate analysis", - "section": "Analysis", - "text": "Analysis\nMCA summarizes the relationships between the categories of the R community variables.\n\nTo interpret the main dimensions of variability in the response profiles, we study the proximities between categories. Indeed, two categories are close on the graph if most respondents taking the first category also take the other category.\n\nFirst dimension of variability\nThe first dimension (horizontal axis) opposes people that didn’t answer questions about involvement in the R community on the left, to the others on the right. More precisely, they did not answer Q21, Q18 and Q20 and did not check any boxes for the other questions (_no). Individuals with the smallest coordinates on the first dimension work more in the industry; this is confirmed by a statistical test, but this remains difficult to interpret.\n\n\nSecond dimension of variability\nOn the top, there are respondents who do not attend an R user group because they feel too inexperienced. They think that they would be more likely to participate in the R community or to improve their experience, if a user group, a workshop, or an online support dedicated to their socio-demographic group would be available. Facebook would be their preferred medium for R community news. They do not use Twitter (question Q19_B), (the category R_twitter_no corresponds to the answer The #rstats hashtag on Twitter for the question Which of the following resources do you use for support?). In addition, they do not like to use it as a medium for R community news (question Q20). They consider themselves as outside the R community.\nOn the bottom, in contrast, there are individuals who tend to consider themselves as part of the R community. They attend general R user group meetings and they use Twitter. Twitter would be their preferred medium for R community news.\n\n\n\nRelationship with demographic\nIn the following graph, answers about the demographic questions are projected as supplementary variables on the two first dimensions of variability. Supplementary variables are not used to build the dimensions of variability, but they are projected a posteriori to highlight relationships between the dimensions of variability and demographics. Thus, supplementary variables can be used to characterize the response profiles described previously.\nOnly demographic characteristics that are significantly related the R community profiles are represented. An analysis of variance with demographic variables as covariates, and the coordinates of the individuals on the dimensions as explanatory variables, has been performed.\n\nIt appears that people having an undergraduate degree or a master degree are located at the top of the graph, while those with a doctorate are at the bottom. This would imply that people with undergraduate degree or master degree are more likely to consider themselves as outside the R community than people having a doctorate. The same comment holds for women versus men. It is interesting to note, caregivers for children or adult dependents tend to be at the bottom of the graph, while non-caregivers are on the top.\nWe represent the age categories on the map since some confounding effects with other demographic variables could explain the previous results. Youngest people tend to be on the top of the second axis, which suggests that they consider themselves as outside the community.\n\nTo get more insights into this possible confounder effect, we created a new variable sex-age and represent it:\n\nIt highlights that both young (men and women) and women do not consider themselves as part of the R community.\n\n\nSimilarities between respondents\nA clustering of the participants is performed from their answers to questions about their involvement in the R community. More precisely a hierarchical clustering is performed on the principal components of MCA. The rationale is to improve the stability of the clustering by building it from denoised data rather than from the original dataset1. Several rules can be used to select the number of components used for the clustering. Here we choose 44 dimensions which corresponds to 95% of the projected inertia (variance) of the data.\nThe number of clusters is chosen according to the barplot of the inertia gains which suggests a partition with 3 clusters. However, this clustering is not relevant since most of respondents are in the same group:\n\n\n\n\n1\n2\n3\n\n\n\n\nsize\n12\n425\n6\n\n\n\nWe investigate the number of respondents in each group according to the number of components used to build the clustering:\n\n\n\n\nclust1\nclust2\nclust3\nclust4\nclust5\nclust6\nclust7\n\n\n\n\nncp=2\n12\n307\n124\n0\n0\n0\n0\n\n\nncp=3\n12\n208\n162\n61\n0\n0\n0\n\n\nncp=4\n12\n231\n139\n61\n0\n0\n0\n\n\nncp=5\n12\n212\n148\n65\n6\n0\n0\n\n\nncp=6\n12\n249\n160\n22\n0\n0\n0\n\n\nncp=7\n12\n269\n159\n3\n0\n0\n0\n\n\nncp=8\n12\n255\n173\n3\n0\n0\n0\n\n\nncp=9\n12\n236\n192\n3\n0\n0\n0\n\n\nncp=10\n12\n271\n157\n3\n0\n0\n0\n\n\nncp=11\n12\n273\n155\n3\n0\n0\n0\n\n\nncp=12\n12\n428\n3\n0\n0\n0\n0\n\n\nncp=13\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=14\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=15\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=16\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=17\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=18\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=19\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=20\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=21\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=22\n12\n425\n6\n0\n0\n0\n0\n\n\n\nWe choose to keep 10 components as this will keep enough information, while highlighting a new cluster in the previous big one.\n\nRespondents are grouped in the clusters as follows:\n\n\n\n\n1\n2\n3\n4\n\n\n\n\n%\n2.71\n61.17\n35.44\n0.68\n\n\n\n\nFrom the previous interpretation of the two first dimensions of variability, the location of clusters on the graph allows providing a brief summary of the clusters: cluster 1 is the group of non-respondents, while cluster 2 contains some respondents who feel they are part of the R community unlike the cluster 3 respondents.\n\nCluster 1\nTo describe the first cluster more precisely, we use statistical tests to compare the proportion of each category in the cluster against the proportion in the population of the respondents.\nUnsurprisingly, there is an over-representation of people that didn’t answer the questions about the involvement in the R community. Using the demographic characteristics, we can see that they are mainly from the industry.\n\n\nCluster 2\nThe following categories are over-represented in cluster 2:\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ24=new_gp_near_no\n78.19\n92.62\n72.46\n< 2e-16\n\n\nQ18=in_Rcommunity_yes\n70.64\n94.10\n81.49\n< 2e-16\n\n\nQ21=Yes\n85.89\n51.66\n36.79\n< 2e-16\n\n\nQ21_new=meeting_yes_A general user group\n86.82\n41.33\n29.12\n1.1e-13\n\n\nQ19_B=R_twitter_yes\n85.59\n37.27\n26.64\n3.4e-11\n\n\nQ24_C=free_workshop_no\n66.75\n94.10\n86.23\n3.1e-09\n\n\nQ20_new=medium_Twitter\n90.00\n23.25\n15.80\n8.3e-09\n\n\nQ19=R_mailing_yes\n73.89\n49.08\n40.63\n4.8e-06\n\n\nQ24_B=new_gp_demo_no\n64.08\n97.42\n93.00\n7.9e-06\n\n\nQ21_new=meeting_no_It is not necessary (I have the support I need)\n96.15\n9.23\n5.87\n3.5e-05\n\n\nQ24_D=paid_workshop_no\n64.92\n91.51\n86.23\n7.5e-05\n\n\nQ19_C=R_StackOverflow_yes\n66.17\n81.55\n75.40\n0.00020\n\n\nQ21_new=meeting_no_I am too busy\n77.92\n22.14\n17.38\n0.00071\n\n\nQ7=Doctorate\n68.91\n49.08\n43.57\n0.00334\n\n\nQ1_new=Q1_new_Academic/Govt\n69.02\n46.86\n41.53\n0.00428\n\n\nQ24_F=demo_workshop_no\n62.65\n97.79\n95.49\n0.00481\n\n\nQ9=Part-time\n93.33\n5.17\n3.39\n0.00648\n\n\nQ7=Professional degree or certification\n100.00\n3.69\n2.26\n0.00687\n\n\nQ19_L_new=web_no\n62.50\n97.79\n95.71\n0.00928\n\n\nQ24_K=online_demo_no\n62.35\n97.79\n95.94\n0.01753\n\n\nQ19_F=Biocond_yes\n80.65\n9.23\n7.00\n0.01900\n\n\nQ2Q3=>58_Men\n85.00\n6.27\n4.51\n0.02259\n\n\nQ3_cat=>58\n81.48\n8.12\n6.09\n0.02320\n\n\nQ2=Men\n65.22\n66.42\n62.30\n0.02582\n\n\nQ2Q3=29-33_Men\n74.14\n15.87\n13.09\n0.02851\n\n\n\nThe numbers read as follows, e.g. for Q18: 70.64% of individuals who consider themselves as part of the R community are in cluster 2; in cluster 2 94.1% of the individuals consider themselves as part of the R community, and 81.49% in the population of all the respondents consider themselves as part of the R community. The test is significant which implies that this cluster can be considered as a cluster with an over-representation of people considering themselves as part of the community. We conclude they are not interested in free workshops, online demos, etc. According to the demographic characteristics, there is an over-representation of people employed permanently in academia, people with caring responsibilities, as well as a significantly larger proportion of men and people with a doctorate.\nWe studied the categories under-represented in the cluster. However, since most of variables are binary, we do not get new information from this table. We note however that young people are under-represented, as well as people who didn’t participate in R user group meetings because of inexperience.\n\n\nCluster 3\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ24=new_gp_near_yes\n81.97\n63.69\n27.54\n< 2e-16\n\n\nQ21_new=meeting_no_There is no group nearby/the group is inactive\n78.82\n42.68\n19.19\n< 2e-16\n\n\nQ21=No\n50.75\n86.62\n60.50\n< 2e-16\n\n\nQ18=in_Rcommunity_no\n76.81\n33.76\n15.58\n2.4e-14\n\n\nQ24_C=free_workshop_yes\n73.77\n28.66\n13.77\n5.9e-11\n\n\nQ21_new=meeting_no_I feel too inexperienced\n90.32\n17.83\n7.00\n7.2e-11\n\n\nQ19_B=R_twitter_no\n43.69\n90.45\n73.36\n2.5e-10\n\n\nQ24_D=paid_workshop_yes\n62.30\n24.20\n13.77\n4.8e-06\n\n\nQ24_B=new_gp_demo_yes\n74.19\n14.65\n7.00\n6.9e-06\n\n\nQ20_new=medium_Website\n52.73\n36.94\n24.83\n1.8e-05\n\n\nQ19=R_mailing_no\n42.97\n71.97\n59.37\n5.6e-05\n\n\nQ19_L_new=web_yes\n68.42\n8.28\n4.29\n0.00351\n\n\nQ20_new=medium_Facebook\n66.67\n8.92\n4.74\n0.00351\n\n\nQ8=Q8_Employed in industry\n42.37\n47.77\n39.95\n0.01354\n\n\nQ3_cat=20-28\n45.83\n28.03\n21.67\n0.01803\n\n\nQ24_F=demo_workshop_yes\n60.00\n7.64\n4.51\n0.02503\n\n\nQ7=Undergraduate degree\n50.00\n15.92\n11.29\n0.02609\n\n\nQ24_K=online_demo_yes\n61.11\n7.01\n4.06\n0.02707\n\n\nQ2Q3=20-28_Women\n50.00\n15.29\n10.84\n0.02974\n\n\nQ20_new=medium_Google+\n100.00\n1.91\n0.68\n0.04396\n\n\nQ7=High school/Secondary school or lower\n100.00\n1.91\n0.68\n0.04396\n\n\n\nIn this cluster, there is an over-representation of those who adhere to most of the proposals to increase their participation in the R community. Most of them have never participated in a user group meeting. The cluster gathers a large number of people who use blogs to get help, but also a large proportion of people who do not use Twitter. They prefer to use a medium like Facebook or mailing lists for news.\nFrom a demographic point of view, the cluster contains a significantly higher proportion of women than the respondent population, and a larger proportion of those with a master’s or undergraduate degree. People under the age of 30 are also over-represented.\nNote that we need to be cautious concerning the interpretation of the clustering as it varies depending on the number of MCA components selected. The stability of the solution should be investigated further. In addition, the number of individuals per cluster may slightly vary as there is a “consolidation step”2 which is applied, i.e. a k-means algorithm applied after the hierarchical clustering." + "text": "The useR! survey received a total of 455 responses out of 904 attendees. Anticipating a high proportion of non-response, questions were included in the survey on participants’ gender, registration type and country of residence, with a view to adjusting observed counts in each cross-classified group to match the proportions in the total useR! 2016 population. Unfortunately the country of residence was not recorded during registration and could not be reliably derived from available information such as affiliation. Although registration type should have been available, in practice it was missing for about one third of participants. This leaves gender, which was (self-)recorded for presenters, but not for other attendees. In order to obtain a gender assignment for all participants, the first names were analysed with the genderizer package, which predicts gender from first name, based on profiles scraped from the web. For participants where the gender was unknown, the genderizer prediction was used if it was based on a sample > 10 and had probability > 0.9, otherwise the gender was assigned based on a manual web search, where this led to a clear assignment. This gave estimates of 235 female, 593 male and 76 undetermined.\nAssuming that the gender distribution is similar in the undetermined group, the survey population overrepresents female attendees by about 10%:\n\n\n\nGender\nSurvey Percentage\nAttendee Percentage\n\n\n\n\nFemale\n37.31\n28.38\n\n\nMale\n62.47\n71.62\n\n\nNon-Binary\n0.22\nNA\n\n\n\n(The assumption that the undetermined have a similar gender distribution seems reasonable, as similar estimates of attendee breakdown were obtained based on genderizer results only, where there were 52.17% undetermined). This over-representation of females is a common phenomenon in surveys and particularly unsurprising here as females may be more motivated to respond to a survey run by the Women in R taskforce." }, { - "objectID": "docs/MCA_community_useR2016_survey/index.html#footnotes", - "href": "docs/MCA_community_useR2016_survey/index.html#footnotes", - "title": "useR! 2016 participants and the R community: a multivariate analysis", - "section": "Footnotes", - "text": "Footnotes\n\n\nFor more details about the classification based on principal components methods, see: Francois Husson, Jerome Pages, Sebastien Le. Exploratory Multivariate Analysis by Example Using R. CRC Press Taylor & Francis, pp.240, 2010, Chapman & Hall/CRC Computer Science & Data Analysis.↩︎\nFor more details about the classification based on principal components methods, see: Francois Husson, Jerome Pages, Sebastien Le. Exploratory Multivariate Analysis by Example Using R. CRC Press Taylor & Francis, pp.240, 2010, Chapman & Hall/CRC Computer Science & Data Analysis.↩︎" + "objectID": "docs/nonresponse_useR2016_survey/index.html#adjusting-for-non-response", + "href": "docs/nonresponse_useR2016_survey/index.html#adjusting-for-non-response", + "title": "Non-response in useR! 2016 Survey", + "section": "Adjusting for non-response", + "text": "Adjusting for non-response\nIn order to adjust for the difference in gender balance between the sample and the full population, weights may be computed for males and females so that the ratio of females to males based on adjusted counts (sum of weights in each category) is equal to that estimated for the full sample. Specifically, the weight for females is 0.76 and the weight for males is 1.14.\nThese weights can then be used in further analysis, for example when tabulating by another survey variable. Here we will consider a few examples for illustration.\n\nAge\nThe unweighted and weighted densities have a very similar shape, but using the weighting shifts the density slightly to the left, i.e. when females are down-weighted there is a slight shift to a generally older population.\n\n\n\nEducation level\nHere there is very little difference between the unweighted and weighted counts.\n\n\n\nQ7\nCount\nAdj.Count\n\n\n\n\nProfessional degree or certification\n10\n10.67\n\n\nDoctorate\n199\n200.69\n\n\nMasters degree\n187\n186.06\n\n\nUndergraduate degree\n52\n50.63\n\n\nHigh school/Secondary school or lower\n3\n3.05\n\n\nNA\n7\n6.90\n\n\n\n\n\nEmployment status\nAgain the differences between unweighted and weighted counts are small here, however there is a consistent shift from less financially secure positions (student, unemployed and employed non-permenantly in academia) to more financially secure positions (employed permenantly in academia, employed in industry). This tallies with the younger distribution of females noted above.\n\n\n\nQ8\nCount\nAdj.Count\n\n\n\n\nEmployed in industry\n183\n186.24\n\n\nEmployed permanently in academia\n76\n78.08\n\n\nEmployed non-permanently in academia\n59\n57.10\n\n\nEmployed in government/non-profit\n70\n69.54\n\n\nSelf-employed\n6\n6.48\n\n\nRetired\n2\n2.29\n\n\nStudent\n44\n40.71\n\n\nUnemployed\n4\n3.42\n\n\nNA\n14\n14.14\n\n\n\n\n\nTime using R\nWith the weighted counts we see a slight shift towards greater experience; this again tallies with females being generally younger and less advanced in their careers.\n\n\n\nQ11\nCount\nAdj.Count\n\n\n\n\n> 10 years\n119\n123.28\n\n\n5-10 years\n132\n132.38\n\n\n2-5 years\n118\n118.05\n\n\n1-2 years\n35\n31.57\n\n\n6-12 months\n29\n28.17\n\n\n< 6 months\n9\n8.76\n\n\nNA\n16\n15.80\n\n\n\n\n\nRecreational use of R\nWith the weighted counts we see a shift towards using R for recreational activity alone or as well as for work. Since the weighting down-weights females relative to males this suggests males are more able or more willing to use R for fun.\n\n\n\n\n\n\n\n\nQ14\nCount\nAdj.Count\n\n\n\n\nFor both recreational and job/educational purposes.\n160\n169.41\n\n\nPrimarily as a recreational activity, in your free time;\n4\n4.58\n\n\nPrimarily as part of a job or educational course;\n275\n265.55\n\n\nNA\n19\n18.46\n\n\n\n\n\nSummary\nThe examples above illustrate that the difference between unweighted and weighted counts tends to be small and is unlikely to affect conclusions drawn about the distribution of a particular variable in the useR! population as a whole.\nWhere there is a material difference between unweighted and weighted counts, this can be attributed to gender, since the weighting only depends on this factor. In this case it would be more interesting to explore the gender difference by showing a summary grouped by gender and then the weighting becomes irrelevant as we are no longer trying to represent the whole population.\nSummarising by gender will necessarily exclude individuals that are non-binary or have not stated their gender. In addition, summarising by gender can result in (more) categories containing only a few individuals, which is undesirable as we wish to protect anonymity. Therefore a grouped summary should only be used when there is a substantive gender difference and small groups can be combined without too much loss of information. First considering the unweighted and weighted counts can help in making this judgement. Using the weights in this exploratory way is perhaps more appropriate than using them to adjust the counts, given that they are based in part on predicted data." }, { - "objectID": "contribution.html", - "href": "contribution.html", - "title": "Contribution", - "section": "", - "text": "The Forwards on-ramps team work on initiatives to support useRs to become developeRs, with a focus on contributing to the R project via packages on CRAN/Bioconductor or via contribution to R Core. Find out more about specific projects below.\n\nFirst Contributions using GitHub/RStudio: Many R packages are version controlled using git and hosted on a platform such as GitHub or GitLab. This enables people from the general R community to submit contributions to packages to fix issues, e.g. to correct a typo in the documentation, to fix a bug or even to propose an improvement or new feature. The first-contributions repository is designed to give first-timers a place to practice the workflow of forking a GitHub repository, making a small change and submitting a pull request back to the original repository for the maintainers to review.\nR Contribution Working Group: This group is a collaboration between R Core, R community groups (including Forwards, the R Consortium Diversity and Inclusion Working Group, R-Ladies, MiR) and members of the wider R community. Its aim is to encourage new contributors to R core, with a focus on diversity and inclusion. See the R Contribution Working Group subsite for more information, including how to join the Slack group for anyone interested in R core contribution.\n\nSee also the Education page, which includes learning resources for useRs wanting to learn about package development." + "objectID": "docs/nonresponse_useR2016_survey/index.html#grouped-summaries", + "href": "docs/nonresponse_useR2016_survey/index.html#grouped-summaries", + "title": "Non-response in useR! 2016 Survey", + "section": "Grouped Summaries", + "text": "Grouped Summaries\nHere we show how the conclusions of the previous section might be applied to our illustrative questions.\n\nAge\nThe difference in density between weighted and unweighted is small but consistent across a wide age range so deserves further exploration. Since we are using a density summary there is no issue with small sub-groups.\nBreaking down by gender shows the difference in age distribution much more clearly:\n\n\n\nEducation level\nAlthough there is some evidence of a more educated male population (weighted counts shift to higher education levels) the difference is small. In addition the numbers without university-level education are very small and even combined with the missing group there is potential that individuals are identified when broken down by gender. Therefore it is best to keep genders combined here and base the final summary on unweighted counts.\n\n\n\nEmployment status\nHere the shift from unweighted counts to weighted counts is larger. Although there are small groups, these can reasonably be combined into an “Other” category.\n\n\n\nTime using R\nAgain there are material differences between unweighted and weighted counts, here the original groups can be left as is:\n\n\n\nRecreational use of R\nHere there is a clear difference between unweighted and weighted counts. As only four people (men) said that they used R primarily as a recreational activity, this can be combined with the missing category:" }, { - "objectID": "community.html", - "href": "community.html", - "title": "Community", - "section": "", - "text": "Forwards partners with community groups within and beyond the R community to work towards more inclusive tech and open source/research software communities.\nThe R community groups with a particular mission to support members of underrepresented groups include:\n\nR-Ladies: the mission of R-Ladies is to achieve proportionate representation by encouraging, inspiring, and empowering people of genders currently underrepresented in the R community.\nAfricaR: working to achieve improved representation by encouraging, inspiring, and empowering the African population of all genders who are underrepresented in the global R community.\nMiR: MiR Community hopes to provide a space of belonging and support for people who identify as underrepresented minority R useRs. They aim to provide opportunities for underrepresented minority useRs to contribute to the R community.\nBlind R User Group: a mailing list for anyone interested in knowing more about (or improving) the use of R by blind people. This would include blind students, their support staff, or anyone having an interest in how blind people will make use of R and related tools.\nRainbow R (R LGBTQ+): a community that supports, promotes and connects LGBTQ+ people who code in the R language.\n\nIn addition, there are many general R User Groups open to all, some of which are listed in the following places:\n\nR Community Explorer a dashboard that tracks meetups listed on Meetup.com.\nR User Group List maintained on GitHub by the R consultancy Jumping Rivers. Others may be found by searching on Meetup or Facebook.\n\nForwards is a taskforce set up by the R Foundation, the not-for-profit organization that supports the R project. Other organizations we work with include:\n\nR Consortium a not-for-profit consortium of business set up to support the worldwide community of users, maintainers and developers of R software.\n\nThe R Consortium has a Diversity & Inclusion Working Group.\n\nWhy R? Foundation a non-governmental organization set up by a team of R enthusiasts coming from both business and academia who aim to support local R communities around the world." + "objectID": "docs/nonresponse_useR2016_survey/index.html#conclusions", + "href": "docs/nonresponse_useR2016_survey/index.html#conclusions", + "title": "Non-response in useR! 2016 Survey", + "section": "Conclusions", + "text": "Conclusions\nWhere there is no material difference between genders, the over-representation of women in the sample is unimportant. Where there is a substantive difference, it is interesting to explore this difference in a grouped summary, where again the over-representation of women becomes irrelevant as males and females are summarised separately.\nTherefore rather than base final summaries on weighted counts, which are based in part on predicted data, it is better to use the weighted counts as a guide to when a grouped summary is appropriate." }, { - "objectID": "blog/2020/southern-africa-project-2020/index.html", - "href": "blog/2020/southern-africa-project-2020/index.html", - "title": "Southern Africa Project 2020", + "objectID": "docs/MCA_programming_useR2016_survey/index.html", + "href": "docs/MCA_programming_useR2016_survey/index.html", + "title": "useR! 2016 participants and R programming: a multivariate analysis", "section": "", - "text": "Using the satRday Johannesburg 2020 conference as a springboard, Forwards set up a project to help build the R community in Southern Africa. With funding from the Why R? Foundation, the R Consortium and a crowd-funding campaign, Forwards collaborated with local R users to run a series of training and community events in South Africa, Eswatini and Botswana. All the events promoted AfricaR, the pan-African network of R users, to help raise awareness of this community among R users in Southern Africa.\n\nSouth Africa\nThe events began with Heather Turner assisting Bianca Peterson in running her 2-day Introduction to R Workshop hosted by PwC, Midrand.\n Bianca Peterson with participants at the Introduction to R workshop, Johannesburg\nThis event was attended by over 20 participants, mostly from local businesses and organizations. Although Bianca and Heather were there because of the satRday, most of the participants were new to R and only came to the workshop. This demonstrates the potential for conferences to facilitate outreach events that grow the community. Due to fantastic support of the crowd-funding campaign, Forwards was able to award a scholarship to Ofentse Phuti-Rice, a Computer Science MSc student from Botswana. The scholarship enabled her to attend this workshop, the Web Scraping with R pre-satRday workshop led by Megan Beckett and Andrew Collier, and the satRday itself.\nAfter the Introduction to R workshop, Heather joined fellow satRday keynote Colin Fay to speak at R-Ladies Johannesburg. Colin spoke on how to contribute to the R ecosystem - everything from sharing what you’re learning to writing a package - while Heather spoke about publishing and promoting your packages. This time the dozen or so attendees were R enthusiasts, most of whom would be at the satRday workshops and/or conference.\n The folks at R-Ladies Johannesburg\nThe satRday workshops were the following day. Heather led a workshop using the latest iteration of the Forwards package development slides, with Bianca assisting. The workshop was open to all, however funding from the R Consortium supported scholarships for four women to attend: Astrid Radermacher, a postdoc at the University of Cape Town; Lillian Pazvakawambwa, a lecturer at the University of Namibia; Fransina Amutenya, a statistician at Namibia Statistics Agency and Caroline Akoth, Advocacy and Operations Lead, Women in GIS, Kenya. The scholarship enabled the recipients to attend the satRday conference as well as the workshop.\n Heather Turner leading the R Package Development workshop, Johannesburg.\nThe satRday itself was attended by over 100 people, with many folk travelling from across South Africa and beyond to attend.\n Participants waiting for the programme to start at satRday Johannesburg.\nThere was a packed programme of 2 keynote talks, 13 regular talks and 8 lightning talks - there are links to slides and videos in the programme. Heather gave a talk on Diversity and Inclusion in the R Community (Video, Slides), focusing on outreach to underrepresented groups beyond white women and the path to becoming an R (core) developer. The conference was also a great opportunity for networking, particularly among people from different cities/countries.\n Emmanuel Ọlámíjùwọ́n, co-organizer of Eswatini UseR group, with Heather Turner, satRday Johannesburg.\n\n\nEswatini\nAfter the satRday, Heather travelled to Eswatini to give a two-day workshop at the University of Eswatini, hosted by the Eswatini UseR group. Participants were mostly students/staff at the university, but a few came from outside organizations such as the revenue authority and a local non-profit. The workshop covered data import, data wrangling, data visualisation and linear modelling, and the participants created an R markdown report based on a case study.\n Participants at Introduction To R workshop, Eswatini, including two of the user group organizers at the back by the windows, L: Garikayi Chemhaka, R: Nontsikelelo Shongwe\nThere was a lot of interest in more advanced topics, such as handling missing data, working with big data and machine learning. At the end of the workshop, Heather gave a talk on the R Community and Free Resources so that participants would know how to get support and materials for further learning.\n Mbongeni Dube, co-organizer of Eswatini UseR group, outside the workshop venue.\n\n\nGaborone\nDue to a flight cancellation (unrelated to COVID-19), Heather was not able to visit Gaborone as planned. However the organizers from the new Botswana R Users group, along with co-organizers from WiMLDS Gaborone and PyData Botswana helped facilitate an Introduction to R tutorial, with Heather teaching remotely over Zoom. The tutorial gave a basic orientation of R/RStudio, before focusing on visualization with base R and ggplot2 (slides here, we skipped data wrangling).\nThe participants took some great photos, including our banner image and the one of women attendees below.\n Women that attended the Introduction To R workshop, Botswana.\nAfter the workshop, the Botswana R User group was officially launched. Heather gave her talk on the R Community and Free Resources, while Edson Kambeu gave an overview of the vision for the R User Group. Attendees took turns to introduce themselves: there were a number of students and people working as statisticians or data scientists; most people currently used SPSS or Python, but were interested to learn R.\n\n\nElsewhere\nThose are all the events that have taken place so far. The original aim was also to run a tutorial and launch a R User Group in Namibia. This proved to be too difficult to arrange to coincide with Heather’s visit to the area, but useful connections were made and organizers at the University of Namibia have applied for a grant from The R Consortium to help launch a user group. There is also some funding left over from the crowdfunder, which we hope to use to support a tutor from South Africa to lead a tutorial in Windhoek, when circumstances allow it. We have also made connections to people interested in R (and QGIS) training in Lesotho and hope to follow that up if we can.\n\n\nSummary\nWe’d like to thank all our supporters that made these events possible, especially the individuals that contributed to the crowdfunder. It was great that we were able to cover all the anticipated costs as well as fund some scholarships to the Johannesburg satRday and pre-conference workshops. The events helped to get many people started with R and hopefully inspired them to continue with it, supported by the local groups and wider community.\n\n\nPhoto credits\nPhotos from Gaborone by meetup attendees.\nPhoto of R-Ladies Johannesburg by Kirsty Lee Garson.\nPhoto of Eswatini UseR group by Emmanual Ọlámíjùwọ́n.\n\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" + "text": "The useR! survey gathers responses to questions on different themes for 455 attendees: demographic characteristics, R programming and involvement in the R community. The separate analyses of each question in each theme are detailed in the posts Mapping useRs, useRs Relationship with R and Community Involvement of useRs. Here, we aim at understanding attendees’ joint responses to the questions of the survey for a given theme. In other words, we would like to highlight the relationships between their answers, as well as to highlight the similarities between the respondents. Multiple correspondence analysis (MCA) is a dimensionality reduction method which allows to explore and visualize a set of categorical variables. It can be seen as the counterpart of PCA for categorical data. The aim of this document is to go beyond univariate analyses and to present the results of a multivariate analyses of the R programming questions using MCA. A corresponding analysis of the R community questions is detailed in a companion report.\n\n\n\nWe base our study on the following questions:\n\n\n\nQ1 What did you register as at useR! 2016?\nQ2 What is your gender?\nQ3 In what year were you born?\nQ4 To what racial or ethnic group(s) do you identify?\nQ5 In what country do you currently reside?\nQ6 Do you identify as LGBT (Lesbian, Gay, Bisexual, Asexual and/or Transgender)?\nQ7 What is the highest level of education you have completed?\nQ8 What is your current (primary) employment status?\nQ9 Is your current job full-time or part-time?\nQ10 Are you a caregiver for children or adult dependents on a regular basis?\n\n\n\n\n\nQ11 How long have you been using R for?\nQ12 Did you have previous programming experience before beginning to use R?\nQ13 Which of the following do you do? Tick any that apply among\n\nQ13A I use functions from existing R packages to analyze data\nQ13B I write R code designed to make my work easier, such as loops or conditionals or functions\nQ13C I write R functions for use by myself or my collaborators\nQ13D I contribute to R packages (on CRAN or elsewhere)\nQ13E I have written my own R package\nQ13F I have written my own R package and released it on CRAN or Bioconductor (or shared it on GitHub, R-Forge or similar platforms)\n\nQ14 Do you use R as a recreational activity, primarily as part of a job or both?\nQ15 How much do you agree or disagree with the following statements?\n\nQ15A Writing R is fun\nQ15B Writing R is considered cool or interesting by my peers?\nQ15C Writing R is a monotonous task\nQ15D Writing R is difficult\n\nQ16 Would you recommend R to friends or colleagues as a programming language to learn?\nQ17 What would be your number one argument for/against learning R?\n\nQuestions Q1-Q10 focus on the demographic characteristics of the respondents while questions Q11, Q13 and Q14 are related to the use of R, and questions Q15 to Q17 to the perception of R. Note that Q12 is about programming in general and not specifically dedicated to R.\nWe first focus on the topic “uses of R” and we will consider the perception questions in a second step. The demographic questions are also used in the analysis in order to help in the interpretation and to describe the profile of R programming answers.\n\n\n\n\nQuestions Q1, Q5 and Q17 have a category of answer Other (please specify). The “free” answers have been gathered in different categories and included as new categories in the questions. The new variables (with more levels) are named Q1_new, Q5_new and Q17_new. In addition, some categories name have been modified to make them easily understandable.\nNote that questions Q13_A to Q13_F are answered by ticking one box indicating that the respondent agrees with the category. Consequently, if a box is unchecked, it is impossible to know if they disagree or if they don’t answer the question. Such responses are recoded as yes if the box is checked and recoded as no otherwise." }, { - "objectID": "blog/2019/workshops-for-women-and-girls/index.html", - "href": "blog/2019/workshops-for-women-and-girls/index.html", - "title": "Workshops for Women and Girls", + "objectID": "docs/MCA_programming_useR2016_survey/index.html#introduction", + "href": "docs/MCA_programming_useR2016_survey/index.html#introduction", + "title": "useR! 2016 participants and R programming: a multivariate analysis", "section": "", - "text": "Thanks to generous funding from the R Consortium, Forwards has offered a series of workshops around the world to support the development of coding skills and to increase the participation of women in the R community. In the last year and a half, more than 10 workshops have engaged more than 100 high school students and women in Australia, New Zealand, Europe and the USA. Information about our series of workshops for women and girls can be found on the Edu section of the Forwards website.\nHere we round up some of the highlights." + "text": "The useR! survey gathers responses to questions on different themes for 455 attendees: demographic characteristics, R programming and involvement in the R community. The separate analyses of each question in each theme are detailed in the posts Mapping useRs, useRs Relationship with R and Community Involvement of useRs. Here, we aim at understanding attendees’ joint responses to the questions of the survey for a given theme. In other words, we would like to highlight the relationships between their answers, as well as to highlight the similarities between the respondents. Multiple correspondence analysis (MCA) is a dimensionality reduction method which allows to explore and visualize a set of categorical variables. It can be seen as the counterpart of PCA for categorical data. The aim of this document is to go beyond univariate analyses and to present the results of a multivariate analyses of the R programming questions using MCA. A corresponding analysis of the R community questions is detailed in a companion report.\n\n\n\nWe base our study on the following questions:\n\n\n\nQ1 What did you register as at useR! 2016?\nQ2 What is your gender?\nQ3 In what year were you born?\nQ4 To what racial or ethnic group(s) do you identify?\nQ5 In what country do you currently reside?\nQ6 Do you identify as LGBT (Lesbian, Gay, Bisexual, Asexual and/or Transgender)?\nQ7 What is the highest level of education you have completed?\nQ8 What is your current (primary) employment status?\nQ9 Is your current job full-time or part-time?\nQ10 Are you a caregiver for children or adult dependents on a regular basis?\n\n\n\n\n\nQ11 How long have you been using R for?\nQ12 Did you have previous programming experience before beginning to use R?\nQ13 Which of the following do you do? Tick any that apply among\n\nQ13A I use functions from existing R packages to analyze data\nQ13B I write R code designed to make my work easier, such as loops or conditionals or functions\nQ13C I write R functions for use by myself or my collaborators\nQ13D I contribute to R packages (on CRAN or elsewhere)\nQ13E I have written my own R package\nQ13F I have written my own R package and released it on CRAN or Bioconductor (or shared it on GitHub, R-Forge or similar platforms)\n\nQ14 Do you use R as a recreational activity, primarily as part of a job or both?\nQ15 How much do you agree or disagree with the following statements?\n\nQ15A Writing R is fun\nQ15B Writing R is considered cool or interesting by my peers?\nQ15C Writing R is a monotonous task\nQ15D Writing R is difficult\n\nQ16 Would you recommend R to friends or colleagues as a programming language to learn?\nQ17 What would be your number one argument for/against learning R?\n\nQuestions Q1-Q10 focus on the demographic characteristics of the respondents while questions Q11, Q13 and Q14 are related to the use of R, and questions Q15 to Q17 to the perception of R. Note that Q12 is about programming in general and not specifically dedicated to R.\nWe first focus on the topic “uses of R” and we will consider the perception questions in a second step. The demographic questions are also used in the analysis in order to help in the interpretation and to describe the profile of R programming answers.\n\n\n\n\nQuestions Q1, Q5 and Q17 have a category of answer Other (please specify). The “free” answers have been gathered in different categories and included as new categories in the questions. The new variables (with more levels) are named Q1_new, Q5_new and Q17_new. In addition, some categories name have been modified to make them easily understandable.\nNote that questions Q13_A to Q13_F are answered by ticking one box indicating that the respondent agrees with the category. Consequently, if a box is unchecked, it is impossible to know if they disagree or if they don’t answer the question. Such responses are recoded as yes if the box is checked and recoded as no otherwise." }, { - "objectID": "blog/2019/workshops-for-women-and-girls/index.html#auckland", - "href": "blog/2019/workshops-for-women-and-girls/index.html#auckland", - "title": "Workshops for Women and Girls", - "section": "Auckland", - "text": "Auckland\nForwards teamed up with the Auckland University Department of Statistics to offer two R workshops in December 2017, one day for women on package development and one day for girls on web app development. Hadley Wickham and Jenny Bryan developed course materials for the package development workshop, while Di Cook developed the materials for the girls’ workshop. Both sets of materials were released under Creative Commons licenses so that they could be reused and adapted for future workshops.\nSee the material for the girls’ workshop and two of the apps developed by the girls to explore New Zealand’s PISA standardised scores: Booknerd’s App and Zoe’s App." + "objectID": "docs/MCA_programming_useR2016_survey/index.html#analysis-of-the-uses-of-r", + "href": "docs/MCA_programming_useR2016_survey/index.html#analysis-of-the-uses-of-r", + "title": "useR! 2016 participants and R programming: a multivariate analysis", + "section": "Analysis of the uses of R", + "text": "Analysis of the uses of R\nThe following graphic summarizes relationships between the answers to the “uses of R” questions. To interpret the main dimensions of variability in the response profiles, we base our analysis on the proximities between categories. Two categories are close on the graph when individuals who have selected the first category also tend to take the other category.\n\nProximities between categories Q11.NA and Q14.NA indicate that people who did not answer Q11 (How long have you been using R for?) often did not answer Q14 (Do you use R as a recreational activity, primarily as part of a job or both?). However, it only concerns 16 individuals.\nWe can see on the graph a gradient which shows the relationship between the question Q11 related to the experience in R programming and the question Q13 related to the use of R, with people on the right, who have recently started using R, and people on the left, who have used R for a long time. In particular, the users with more than 10 years’ experience have already written their own package or contributed to packages, while people with less than 2 years’ experience haven’t. The gradient can be clearly interpreted and shows the progression in gaining new skills.\nThe beginners in R seem to be trying R during their free time. This is less true for experienced users who have probably gained their experience during their job. Note that beginners in R are very few among respondents (9 people with less than 6 months’ experience).\nThe graph of the individuals allows identification of the individuals located at the top right who do not answer some questions. These individuals did not answer any of the questions related to their use of R but answered the demographic questions. Interestingly, one of them indicated they just discovered R (in the text answer Q25). This explanation could also be valid for the other ones, explaining why they agree to participate to the study, yet only answer a few questions. This comment is in line with the previous graph, in which categories NA are on the right, which is the location of inexperienced users." }, { - "objectID": "blog/2019/workshops-for-women-and-girls/index.html#budapest", - "href": "blog/2019/workshops-for-women-and-girls/index.html#budapest", - "title": "Workshops for Women and Girls", - "section": "Budapest", - "text": "Budapest\nUsing the material developed for Auckland, Isabella Gollini and Heather Turner ran a package development workshop for women at eRum 2018. Thanks to support from the R Consortium and the eRum conference, eight women were funded to attend the workshop and given free conference registration, with representatives from Denmark, Georgia, Germany, India, Sweden and the UK. Other eRum participants were also able to attend.\n\n\n\nWomen in group discussions at the Budapest package development workshop" + "objectID": "docs/MCA_programming_useR2016_survey/index.html#analysis-of-the-perception-of-the-r-programming-language", + "href": "docs/MCA_programming_useR2016_survey/index.html#analysis-of-the-perception-of-the-r-programming-language", + "title": "useR! 2016 participants and R programming: a multivariate analysis", + "section": "Analysis of the perception of the R programming language", + "text": "Analysis of the perception of the R programming language\n\nThe analysis of questions related to the perception of the R language (Q15, Q16, Q17) shows again that attendees who did not answer one question often did not answer others (1st dimension). More interestingly, the second dimension of the graph highlights that people thinking very strongly that R is monotonous also think that it is not fun, not cool, or even think R is poor. It highlights that among respondents there is a sub-population of people who do not appreciate R. However, it concerns around 10 individuals.\nInterestingly, these respondents tend to recommend R to a friend as a programming language to learn, so that they recognize some interest." }, { - "objectID": "blog/2019/workshops-for-women-and-girls/index.html#new-york-city", - "href": "blog/2019/workshops-for-women-and-girls/index.html#new-york-city", - "title": "Workshops for Women and Girls", - "section": "New York City", - "text": "New York City\nEmily Dodwell and Joyce Robbins taught the first Forwards high school girls workshop in the United States in October 2018 at AT&T in New York City. Sixteen motivated, curious, and dedicated students worked diligently throughout a morning session to tackle an introduction to R, plots in ggplot2, Markdown, and manipulating data with dplyr. Breakout groups over a lunch of pizza and salad discussed careers in data science; volunteers shared their career trajectories, and students asked questions and shared their experiences in high school STEM courses and extracurricular activities.\nThe six-hour workshop culminated in an afternoon hackathon, the theme of which was transportation in and around NYC. Each pair of students chose one of three publicly available datasets—NYC Flights, Taxis, and CitiBike—to explore using the R skills they learned earlier in the day. They then gave a five-minute presentation highlighting visualizations they created that captured interesting behavior or answered questions they formulated.\nMany thanks to the volunteers from AT&T Labs Research, Cheryl Flynn and Ritwik Mitra, and from R-Ladies NYC, Soumya Kalra and Angeline Protacio.\n\n\n\nWorking photo at the New York City Forwards girls’ workshop" + "objectID": "docs/MCA_programming_useR2016_survey/index.html#perception-and-uses-of-r", + "href": "docs/MCA_programming_useR2016_survey/index.html#perception-and-uses-of-r", + "title": "useR! 2016 participants and R programming: a multivariate analysis", + "section": "Perception and uses of R", + "text": "Perception and uses of R\nDoes the perception of the R language differ according to the experience of the user? To answer this question, the perception variables are projected as supplementary variables on the graph obtained with the “uses of R” variables. Supplementary variables are not used to build the dimensions of variability, they are projected a posteriori and help for the interpretation.\n\nWe note that experienced users particularly appreciate R. They find that R is fun, not monotonous and they recommend to use it." }, { - "objectID": "blog/2019/workshops-for-women-and-girls/index.html#chicago", - "href": "blog/2019/workshops-for-women-and-girls/index.html#chicago", - "title": "Workshops for Women and Girls", - "section": "Chicago", - "text": "Chicago\n\n\n\nGroup photo of women at the Chicago package development workshop\n\n\nAngela Li and Stephanie Kirmer, both of R-Ladies Chicago, organized a women’s package workshop in February 2019 for 30 women at the Center for Spatial Data Science in Chicago. This marked the first time an R-Ladies group had run the full package development workshop. The workshop brought women from 11 states in the US to freezing-cold Chicago to learn how to develop their first package. The workshop was preceded by an R-Ladies get-together with an R-Ladies purple cake, where workshop participants from out-of-town were able to get to know each other.\n\n\n\nGroup photo of women at the R-Ladies get-together behind a table with a large iced purple cake\n\n\nPre and post-survey results from the workshop can be found online (thank you, Stephanie, for putting this together!). For a more in-depth look at the event, Josephine Lukito and Florencia Mangini both wrote fantastic recaps of the workshop. You can also find tweets from the event under the hashtag #RForwardsChi on Twitter.\nThanks to the R Consortium, funding was provided for 9 women from California, Tennessee, New York, Wisconsin, and more to attend this workshop. Thanks also to Katherine Simeon, Ola Giwa, and Nichole Burke for being helpers at this event." + "objectID": "docs/MCA_programming_useR2016_survey/index.html#relationship-with-demographic", + "href": "docs/MCA_programming_useR2016_survey/index.html#relationship-with-demographic", + "title": "useR! 2016 participants and R programming: a multivariate analysis", + "section": "Relationship with demographic", + "text": "Relationship with demographic\n\nDemographic variables are also projected as supplementary variables. We excluded the ethnic group variable (Q4) and the country of residence variable (Q5) because of the large number of infrequent categories. The graph above shows that the demographic characteristics are significantly related to the user profiles. An analysis of variance with demographic variables as covariates, and the coordinates of the individuals on the dimensions as explanatory variables, has been performed1. The graph shows that people with a doctorate are more highly represented among advanced users. This also shows that men are more highly represented than women among the most advanced users. As stated in the post useRs Relationship with R, it could be explained by the fact that women tend to be younger, but here we note that the variable Age does not significantly explain the coordinates of the individuals on the graph. To get more insight into this possible confounding effect, we created a variable sex-age and represent it. The plot confirms that men are over-represented amongst the advanced users." }, { - "objectID": "blog/2019/workshops-for-women-and-girls/index.html#brisbane", - "href": "blog/2019/workshops-for-women-and-girls/index.html#brisbane", - "title": "Workshops for Women and Girls", - "section": "Brisbane", - "text": "Brisbane\nForwards teamed up with ACEMS to organise the Brisbane Coding Workshop for Girls held at River City Labs (https://www.rivercitylabs.net) in March 2019. There were approximately 10 girls and 5 helpers. The girls worked on instructional material to get up and running with R and the tidyverse (https://ebsmonash.shinyapps.io/sunny_tutorial/) in the morning. After a pizza lunch, the girls experimented with developing their own shiny app. A theme for the afternoon was “break it, fix it, break it, fix it, …” to encourage experimenting and trying new things. The girls used data from the Atlas of Living Australia, on wildlife sightings around Brisbane, as the basis for the app. There is an R package to interface with this extraordinary data resource. For examples of the apps developed see Claudia’s App and Rachel’s App.\n\n\n\nThe view into River City Labs where the Brisbane girls coding workshop was held, with the girls and leaders chatting at the pizza lunch" + "objectID": "docs/MCA_programming_useR2016_survey/index.html#similarities-between-respondents", + "href": "docs/MCA_programming_useR2016_survey/index.html#similarities-between-respondents", + "title": "useR! 2016 participants and R programming: a multivariate analysis", + "section": "Similarities between respondents", + "text": "Similarities between respondents\nThe participants are clustered according to their answers to the uses of R questions only (Q11, Q13, Q14). To do this, a hierarchical clustering is performed on K principal components of the MCA. The rationale is to improve the stability of the clustering by building it from denoised data.\nSeveral rules can be used to select the number of components used for the clustering. Here we choose 12 dimensions which corresponds to 95% of the projected inertia (variance) of the data.\n\nThe number of clusters is chosen according to the barplot of the inertia gains2 which suggests 3 clusters.\nHowever, since a cluster with non-respondents is expected, we consider 4 clusters to have a more interpretable clustering.\n\nThe first cluster located on the left represent the experienced users while the second cluster gathers the intermediate users and the third one the beginners. The fourth cluster is constituted with people who did not answer.\nThe size of each cluster is as follows:\n\n\n\n\n1\n2\n3\n4\n\n\n\n\nsize\n171\n260\n11\n13\n\n\n\ni.e. in terms of proportions:\n\n\n\n\n1\n2\n3\n4\n\n\n\n\nproportion\n0.38\n0.57\n0.02\n0.03\n\n\n\nWe now interpret the clusters.\n\nCluster 1\nTo help us describing the first cluster, we use statistical tests to compare the proportion of each category in the cluster versus the proportion in the population of the respondents. Of course, for variables that have been used to build the clusters (Q11, Q13, Q14), this test is only indicative, but for others (demographic questions or perception questions), the p.values can be interpreted.\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ13_F=rel_pkg_yes\n96.77\n87.72\n34.07\n< 2e-16\n\n\nQ13_D=ctb_pkg_yes\n88.37\n88.89\n37.80\n< 2e-16\n\n\nQ13_E=wrt_pkg_yes\n71.85\n100.00\n52.31\n< 2e-16\n\n\nQ13_C=wrt_func_yes\n42.93\n97.66\n85.49\n3.5e-10\n\n\nQ13_B=wrt_code_yes\n42.35\n97.08\n86.15\n1.4e-08\n\n\nQ2=Men\n46.64\n77.19\n62.20\n2.2e-07\n\n\nQ7=Doctorate\n50.75\n59.06\n43.74\n3.5e-07\n\n\nQ11=> 10 years\n57.14\n39.77\n26.15\n4.6e-07\n\n\nQ15=fun_Strongly agree\n49.54\n62.57\n47.47\n5.7e-07\n\n\nQ14=For both recreational and job/educational purposes.\n52.50\n49.12\n35.16\n1.7e-06\n\n\nQ1_new=Q1_new_Academic/Govt\n46.81\n51.46\n41.32\n0.00071\n\n\nQ8=Q8_Employed non-permanently in academia\n57.63\n19.88\n12.97\n0.00089\n\n\nQ8=Q8_Employed permanently in academia\n53.95\n23.98\n16.70\n0.00157\n\n\n\nThe table can be interpreted as follows:\n\nfirst row indicates that 96.77% of individuals that have released their own R package are in cluster 1; 87.72% of individuals in this cluster have released their own R package, and 34.07% of individuals in the population have released their own R package.\n\nrow 7 indicates that 50.75% of individuals with a doctorate are in this cluster; 59.06% of individuals in this cluster have a doctorate, and 43.74% of individuals in the population have a doctorate. We can reject at risk 3.47e-07 the null hypothesis the proportion of respondents with a doctorate in the first cluster is the same than the proportion in the population of the respondents. This first table only represents the results when the proportion in the cluster is larger than the proportion in the population.\n\nTo wrap-up, the tests results confirm that cluster 1 gathers experienced users. In this cluster, there is an over-representation of people with a doctorate, men, or people employed in academia. It is also a cluster where the proportion of people strongly seeing R programming as fun is large. In the same line, people in cluster 1 are more likely to use R for both recreational and job/educational purposes.\nThis second table represents the categories that are underrepresented in cluster 1.\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ13_F=rel_pkg_no\n7.00\n12.28\n65.93\n< 2e-16\n\n\nQ13_D=ctb_pkg_no\n6.71\n11.11\n62.20\n< 2e-16\n\n\nQ13_E=wrt_pkg_no\n0.00\n0.00\n47.69\n< 2e-16\n\n\nQ13_C=wrt_func_no\n6.06\n2.34\n14.51\n3.5e-10\n\n\nQ13_B=wrt_code_no\n7.94\n2.92\n13.85\n1.4e-08\n\n\nQ11=6-12 months\n0.00\n0.00\n6.37\n6.6e-07\n\n\nQ2=Women\n23.08\n22.81\n37.14\n6.6e-07\n\n\nQ1_new=Q1_new_Industry\n26.46\n29.24\n41.54\n3.3e-05\n\n\nQ8=Q8_Employed in industry\n26.23\n28.07\n40.22\n3.7e-05\n\n\nQ14=Q14.NA\n0.00\n0.00\n3.52\n0.00045\n\n\nQ11=1-2 years\n11.43\n2.34\n7.69\n0.00046\n\n\nQ7=Masters degree\n28.34\n30.99\n41.10\n0.00065\n\n\nQ14=Primarily as part of a job or educational course;\n31.64\n50.88\n60.44\n0.00131\n\n\nQ11=Q11.NA\n0.00\n0.00\n2.86\n0.00196\n\n\nQ5=United States\n32.91\n60.82\n69.45\n0.00217\n\n\n\nUS people are under-represented in cluster 1. We can imagine that only people deeply using R are motivated to go to the US for such a conference due to the costs.\n\n\nCluster 2\nCluster 2 can be described as a cluster of intermediate users who use R since 1-2 years or less, but more than 6 months. They use R functions, but don’t write their own functions or packages. They appreciate R, but use it primarily for their job. They are more employed in the industry. This cluster gathers more women, more undergraduate and master and people from the US.\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ13_F=rel_pkg_no\n85.33\n98.46\n65.93\n< 2e-16\n\n\nQ13_D=ctb_pkg_no\n85.51\n93.08\n62.20\n< 2e-16\n\n\nQ13_E=wrt_pkg_no\n89.86\n75.00\n47.69\n< 2e-16\n\n\nQ11=6-12 months\n100.00\n11.15\n6.37\n4.4e-08\n\n\nQ14=Primarily as part of a job or educational course;\n66.91\n70.77\n60.44\n2.2e-07\n\n\nQ2=Women\n71.60\n46.54\n37.14\n1.4e-06\n\n\nQ11=1-2 years\n88.57\n11.92\n7.69\n4.0e-05\n\n\nQ8=Q8_Employed in industry\n67.76\n47.69\n40.22\n0.00017\n\n\nQ1_new=Q1_new_Industry\n67.20\n48.85\n41.54\n0.00026\n\n\nQ15=fun_Agree\n67.20\n48.08\n40.88\n0.00031\n\n\nQ7=Masters degree\n66.31\n47.69\n41.10\n0.00096\n\n\nQ2Q3=20-28_Women\n79.07\n13.08\n9.45\n0.00185\n\n\nQ16=rcmd_Yes\n59.09\n95.00\n91.87\n0.00558\n\n\nQ2Q3=29-33_Women\n75.56\n13.08\n9.89\n0.00786\n\n\nQ5=United States\n61.08\n74.23\n69.45\n0.01118\n\n\nQ13=use_func_yes\n58.63\n95.38\n92.97\n0.02258\n\n\nQ7=Undergraduate degree\n71.15\n14.23\n11.43\n0.02953\n\n\nQ15_D=difficult_Disagree\n62.56\n50.77\n46.37\n0.03045\n\n\nQ2Q3=>58_Men\n80.00\n6.15\n4.40\n0.03401\n\n\nQ10=Caryng_resp_No\n60.18\n76.15\n72.31\n0.03569\n\n\n\n\n\nCluster 3\nCluster 3 gathers respondents with less than 6 months of experience in R. They do not have an opinion about the “fun” or “monotonous” nature of R. They use R in their free time and find that the main advantage of R is that it is an open source software. This cluster gather curious users discovering R in their free time. No demographic characteristics show-up in this group.\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ11=< 6 months\n100.00\n81.82\n1.98\n< 2e-16\n\n\nQ14=Primarily as a recreational activity, in your free time;\n100.00\n36.36\n0.88\n1.9e-07\n\n\nQ13_C=wrt_func_no\n12.12\n72.73\n14.51\n1.6e-05\n\n\nQ13_B=wrt_code_no\n11.11\n63.64\n13.85\n0.00016\n\n\nQ15=fun_No opinion\n13.33\n36.36\n6.59\n0.00400\n\n\nQ16=rcmd_No\n14.29\n27.27\n4.62\n0.01195\n\n\nQ15_C=monotonous_No opinion\n7.46\n45.45\n14.73\n0.01564\n\n\nQ4=Native American\n100.00\n9.09\n0.22\n0.02418\n\n\nQ17_new=Open source\n11.11\n27.27\n5.93\n0.02484\n\n\nQ13_E=wrt_pkg_no\n4.15\n81.82\n47.69\n0.02518\n\n\n\n\n\nCluster 4\nAs expected, cluster 4 not described in detail here is a cluster where individuals do not answer questions, or do not check boxes.\n\n\nTo sum-up\nThe respondents can be classified in 3 clusters according to their uses of R:\n\nThe experienced users (38%): they have an in depth knowledge of R programming, even creating their own package. They are mainly men, academic, with a doctorate\nThe intermediate users (57%): they mainly use functions from existing packages, but do not write their own functions. They are mainly women, people from industry, who are undergraduate or have a master degree. In addition, they are more likely from US.\nThe curious users (3%): they have discovered R very recently. They don’t have an opinion that is already formed. They appreciate the open source nature of R.\n\nA fourth cluster of people that didn’t answer the question could be considered. It represents 2% of individuals. They could be potential future users that didn’t have any experience in R at the moment to complete the questionnaire." }, { - "objectID": "blog/2019/workshops-for-women-and-girls/index.html#resources", - "href": "blog/2019/workshops-for-women-and-girls/index.html#resources", - "title": "Workshops for Women and Girls", - "section": "Resources", - "text": "Resources\nMaterials for Forwards workshops can be found in our workshops repository. Additional materials can be found in the teaching_examples repository or linked from our Education page. All Forwards workshop materials are licensed with a Creative Commons license to encourage reuse by the community - please check the exact license on the material, in some cases, there is a restriction to non-commercial use.\nIf you are interested in organizing a workshop of your own, please take a look at the Template Forwards Workshop Google Drive for materials you can use to coordinate logistics for your workshop! This was put together by the Chicago workshop organizers and is something the teaching team plan to build on to support workshop organizers." + "objectID": "docs/MCA_programming_useR2016_survey/index.html#conclusions", + "href": "docs/MCA_programming_useR2016_survey/index.html#conclusions", + "title": "useR! 2016 participants and R programming: a multivariate analysis", + "section": "Conclusions", + "text": "Conclusions\nMissing values often occur on all the R programming questions. One possible explanation backed-up by the free text answer of one individual and by the proximity to the inexperienced users, is that the values are missing because the participants do not program in R. If so, the deletion of missing individuals for subsequent analyses would reduce the scope of the analysis since the sample would be restricted to R users only. However, the cluster of individuals who do not answer these questions, do not answer any of the R community questions as well. Consequently, it can also be individuals who have started answering the questions and stopped before finishing. So we decide to delete this group for the other analyses.\n\nPractices of R are linked to the experience of the users. In particular, users with more than 10 years’ experience have already written their own package, while people with less than 2 years’ experience haven’t.\nA focus on the demographic characteristics of the participants highlights experienced users are more likely men than women, more likely from academia than from industry and more likely people with a doctorate than without. They often use R both for their job and for pleasure. Intermediate users use R for less than 2 years, they mainly use existing packages. Intermediate users are mainly women, people with undergraduate and master degrees and less men or people with doctoral degrees. Beginners are trying R during their free time.\nTo conclude, we should suggest using “yes” and “no” answers for the checkboxes to distinguish missing values from “no”. In addition, we should be cautious about over-interpretation and keep in mind that their is a strong age effect: there are many women who are young." }, { - "objectID": "blog/2019/rladies-charlottesville-workshop-recap/index.html", - "href": "blog/2019/rladies-charlottesville-workshop-recap/index.html", - "title": "Recap of R-Ladies Charlottesville Forwards Workshop", - "section": "", - "text": "On September 8, 2019, Samantha Toet and Angela Li co-taught a 3-hour Forwards Package Development Workshop at a weekend R-Ladies Charlottesville Meetup.\nThe workshop took place as a result of Angela being in town - she reached out to Sam and suggested the workshop, Sam thought it was a good idea, and they worked together to coordinate the logistics (all Sam!) and teaching. By using the Forwards curriculum and pre-made organizing templates - with a few tweaks of their own, of course - they were able to pull together the workshop in a month.\nThe workshop was an abbreviated version of the full Forwards curriculum that allowed participants to develop their first-ever package. The workshop started with motivating the need to create a package, then walked through making a package from scratch, then went over best practices and sharing out a package. We thought it was a good “story arc” for participants: create, document, test, and share.\nWe enjoyed teaching the workshop, and there were several things we learned from teaching it:\n\nLet them eat cake (first), or have participants create and explore their own package, no matter how small it is. You can help with some of the heavy lifting by providing sample functions to use in the package, but give them ownership of the full process.\nMistakes are good! Coding is never perfect or streamlined, so by troubleshooting on the spot, you’re demonstrating the iterative process. For example, Sam started off her session by live troubleshooting a Roxygen tagging issue. Participants could call out their suggestions and collaboratively come to a solution. Participants were also able to get a real taste of the process of looking at help pages, changing some part of the code, re-documenting and building the package, and looking at the results.\nFocus on workflows and process over exact tooling. The goal of this workshop was not to make every participant an expert package developer, but help participants see the patterns of package development. By internalizing these patterns (for example, modify code -> load -> explore in console, or write tests -> modify code -> load), participants are able to understand the general workflow and start to ask deeper questions and explore more on their own.\n\nIf you’re interested in organizing an R-Ladies based workshop of your own, you can use the resources we developed. Please don’t hesitate to reach out to either of us for more information - we’d be happy to chat (or maybe even co-teach)!\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" + "objectID": "docs/MCA_programming_useR2016_survey/index.html#footnotes", + "href": "docs/MCA_programming_useR2016_survey/index.html#footnotes", + "title": "useR! 2016 participants and R programming: a multivariate analysis", + "section": "Footnotes", + "text": "Footnotes\n\n\nFor more details about the use of analysis of variance to interpret the MCA graphs, see: Francois Husson, Jerome Pages, Sebastien Le. Exploratory Multivariate Analysis by Example Using R. CRC Press Taylor & Francis, pp.240, 2010, Chapman & Hall/CRC Computer Science & Data Analysis.↩︎\nFor more details about the classification based on principal components methods, see the reference above.↩︎" }, { - "objectID": "blog/2018/havanar/index.html", - "href": "blog/2018/havanar/index.html", - "title": "HavanaR Workshop 2018", + "objectID": "data.html", + "href": "data.html", + "title": "Data", "section": "", - "text": "The first meeting of R users in Cuba, HavanaR! Club 2018, will take place from 29-10-2018 to 02-11-2018. The workshop is organized jointly by the Group of Probability and Statistics of Universidad de La Habana, the >eR-Biostat initiative, the Center for Statistics, CenStat & I-Biostat, Hasselt University, Belgium and Forwards.\nThe workshop will focus on visualisation methods and exploratory analysis of high dimensional and multivariate datasets.\nProgram:\n29-Oct: Basic concepts of exploratory data analysis using R. Exploratory Analysis of high dimensional data using R (Adetayo Kasim, Durham University, UK, a.s.kasim@durham.ac.uk and Ziv Shkedy, Hasselt University, Belgium, ziv.shkedy@uhasselt.be).\n30-Oct: Exploratory Analysis of high dimensional data using R (Adetayo Kasim and Ziv Shkedy).\n31-Oct: HavanaR! Club 2018: The Cuban R users workshop with presentations of the participants.\n01-Nov: Exploratory Multivariate Data Analysis using R (Julie Josse, Ecole Polytechnique, France, julie.josse@polytechnique.edu).\n02-Nov: Exploratory Multivariate Data Analysis using R (Julie Josse).\nThe workshop is free but registration in mandatory. To register please send an email to erbiostat@gmail.com or cbouza2002@gmail.com.\nMore details and workshop materials will be available online at https://er-biostat.github.io/Courses/. All updates about the workshop will be anounced on the Facebook page (https://www.facebook.com/ER-BioStat-1463845487001786/) and Twitter (@erbiostat).\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" + "text": "The survey sub-team is focused on monitoring diversity and exploring obstacles, motivations, and involvement of useRs in the community. Diversity will be monitored via basic demographic summaries from specifically designed surveys or other community surveys (e.g. useR! feedback survey).\n\n\n\nThe taskforce collates data on the gender breakdown and other demographics of contributors to the R project, particularly R Foundation supported activities. For many of the gender summaries the gender was predicted based on first name, giving a rough approximation that assumes binary gender categories." }, { - "objectID": "blog/2017/users-participation-in-the-r-community/index.html", - "href": "blog/2017/users-participation-in-the-r-community/index.html", - "title": "useRs Participation in the R Community", + "objectID": "data.html#overview", + "href": "data.html#overview", + "title": "Data", "section": "", - "text": "In our first and second posts on the useR! 2016 survey we discussed the responses from the demographic and programming sections. The main findings were:\nIn this last blog post of the series, we consider useRs involvement in the wider R community." + "text": "The survey sub-team is focused on monitoring diversity and exploring obstacles, motivations, and involvement of useRs in the community. Diversity will be monitored via basic demographic summaries from specifically designed surveys or other community surveys (e.g. useR! feedback survey).\n\n\n\nThe taskforce collates data on the gender breakdown and other demographics of contributors to the R project, particularly R Foundation supported activities. For many of the gender summaries the gender was predicted based on first name, giving a rough approximation that assumes binary gender categories." }, { - "objectID": "blog/2017/users-participation-in-the-r-community/index.html#summary", - "href": "blog/2017/users-participation-in-the-r-community/index.html#summary", - "title": "useRs Participation in the R Community", - "section": "Summary", - "text": "Summary\nA large proportion of useR! attendees feel that they belong to the R community, with the proportion increasing with length of time using R.\nStackoverflow and the R mailing lists are the most common resources used for support, despite the negative experience of some useRs. A third of useRs attend a local user group, although the proportion is higher among men than women. The main reasons for not attending are there is no group nearby, or people are too busy. The top initiatives that would encourage more involvement are a new user group nearby and mentoring. Women are more likely than men to want additional support and are more in favour of online support and initiatives targeted at their demographic.\nThe respondents had many suggestions for improving the R community and these along with the other survey responses provide a basis for Forwards and other R community leaders to work towards greater engagement." + "objectID": "data.html#packages", + "href": "data.html#packages", + "title": "Data", + "section": "Packages", + "text": "Packages\n\nMaintainer Demographics 2017\nIn Pinto, Wiese & Dias (2018). How Do Scientists Develop Scientific Software? An External Replication, the authors surveyed CRAN maintainers that self-identified as a scientist. The survey was conducted starting in late November 2017 and ending in early January 2018. The respondents were contacted by email and asked to complete an online questionnaire, with a response rate of 24% (a total of 1,553 responses).\n\nIn 2017, 11.0% of package maintainers who self-identified as scientists were women or non-binary.\n\n\n44.6% of respondents self-identified between 30 and 40 years of age at the time of the survey.\nOverwhelmingly, 80.0% of respondents self-identified as either having a completed or in-progress doctorate degree.\n16.5% of the respondents self-identified as being located outside of Europe and North America.\n\n\n\n\n\n\n\n\n\n\n\n\n\nAuthor Demographics 2010\nMair, P., Hofmann, E., Gruber, K., Hatzinger, R., Zeleis, A. and Hornik, K. (2015) Motivation, values, and work design as drivers of participation in the R open source project for statistical computing, PNAS describes the feedback from 1087 R package authors. The survey was conducted in 2010. Package authors were contacted by email and asked to complete a web form, with a response rate of 27%.\n\nIn 2010, 9% of package authors were women.\n\n\nThe 95% confidence interval for the proportion of women package authors in 2010 is 7.1-11.0%.\n32.5% of authors are from the USA, but they are distributed across the globe, including Indonesia, Kenya, Slovenia and Singapore.\nThe average package author was almost 39 years old, 50% of authors are between 30 and 45, and the youngest was 20." }, { - "objectID": "blog/2017/users-participation-in-the-r-community/index.html#survey-results", - "href": "blog/2017/users-participation-in-the-r-community/index.html#survey-results", - "title": "useRs Participation in the R Community", - "section": "Survey results", - "text": "Survey results\n\nBelonging to the Community\nThe first question asked useRs whether they considered themselves to be part of the R community: 361 (79%) said yes, 69 (15%) said no and 28 (6%) did not give an answer. There was no significant difference in responses from men and women.\nIt’s encouraging that such a large proportion feel part of the R community: as might be expected the proportion increased with the length of time the respondent had used R, yet even people with less than 6 months’ experience responded positively. This is a testament to a generally welcoming community as backed up by some of the free text comments, for example:\n\nY’all seem to have a very active and robust community - keep it up!" + "objectID": "data.html#conferences", + "href": "data.html#conferences", + "title": "Data", + "section": "Conferences", + "text": "Conferences\nData is being collated on past useR! conferences, the plots below show the data gathered so far.\n\n\n2016 saw a rise in the proportion of female attendees from 19% to 28%.\n\nThe proportion of contributed presentations is similar to the proportion of female attendees, showing that women are as likely to contribute and have their contributions accepted as their male counterparts. There was a greater increase in poster contributions from women than lightning or regular talks in 2016, which perhaps reflects a lower level of experience among the newcomers.\nPlot c shows groups that are more heavily selected. The numbers of female invited speakers has increased from zero in the early years (2004-2008) through one in later years (2009-2013) to two in recent years - this is the level that useR! is seeking to maintain for now. The number of tutorials with a female tutor was decreasing since 2007, but went up again to 1/3 in 2016. This is the target for 2017. useR! does not always have panel sessions, but apart from a panel in 2014 on women in the R community, women have been poorly represented. This is something useR! plans to address in any future panels.\nThe last plot shows invited organisational roles. Data on session chairs is only available for a few years, but recently the proportion of women has been similar that of attendees. The proportion of female committee members has been slowly rising to parity over the history of useR! (with an unusual high in 2007 when Di Cook, a taskforce member was a key organiser). The make-up of the local organising committee is much more variable, partly because the size of the committee changes a lot according to local needs. In recent years the proportion of women on the committee has been similar to or greater than that of attendees." }, { - "objectID": "blog/2017/users-participation-in-the-r-community/index.html#conclusions", - "href": "blog/2017/users-participation-in-the-r-community/index.html#conclusions", - "title": "useRs Participation in the R Community", - "section": "Conclusions", - "text": "Conclusions\nIt has taken us a while to work through the survey and report back. However a benefit of this is we can see that actions in the meantime by Forwards and the wider community are already starting to address many of the issues raised in the last part of the survey.\nThe massive expansion of R-Ladies over the past year (from 4 groups to over 452) means that many people who were looking for a group now have one nearby, or will have soon. Many of the suggestions for useR! are in place for useR! 2017: there will be a newbies session, childcare and a “hackathon space” for informal birds of a feather gatherings. In addition 26 participants were awarded diversity scholarships (thanks to the conference sponsors, especially platinum sponsors Microsoft, Open Analytics, R Consortium, RStudio, DataCamp, and IBM).\nWith regards to education and outreach, the Forwards Teaching sub-team were recently awarded an R Consortium grant to develop workshops specifically targeting women and high school girls - initial workshops are planned for September and December in Melbourne, Australia and Auckland, New Zealand respectively. Further workshops will be run in Europe and the US, and the material made available under a Creative Commons share-alike license for others to use.\nBeyond this, we can use the ideas and findings here to inform future initiatives. For example the Forwards Community sub-team can help to promote local groups by raising awareness, connecting people that want to start new groups and sharing ideas to increase participation. In line with our mission to increase participation among under-represented groups, we can focus on initiatives that appear to be particularly appealing to women, such as mentoring and an online forum.\nOverall we have learnt a lot from our survey of useR! participants. In future we would like to study other populations and have package authors in mind for our next big survey. However, we still wish to monitor participation of under-represented groups at useR! so will be running a demographic survey as part of the general conference evaluation survey at useR! 2017. If you’re coming to useR! please support us by responding!" + "objectID": "conferences.html", + "href": "conferences.html", + "title": "Conferences", + "section": "", + "text": "Forwards works to promote diversity and inclusion at R community conferences, especially useR!, the main R conference organized by the R Foundation.\nIn 2016 we made a series of recommendations, which have led to many improvements\n\nincreased representation of women in invited roles (speakers, program committee, session chairs)\nincreased representation of women in contributed program and attendees\nnewcomer-focused sessions since 2017 (excluding 2020 due switching to a virtual event)\ndiversity scholarships since 2016\nchildcare since 2017\ncode of conduct from 2016, with standard code of conduct adopted in 2020\n\nMore recently, we have been focusing on global representation and accessibility for people with disabilities." }, { - "objectID": "blog/2017/users-participation-in-the-r-community/index.html#notes", - "href": "blog/2017/users-participation-in-the-r-community/index.html#notes", - "title": "useRs Participation in the R Community", - "section": "Notes", - "text": "Notes\nNow that we have completed this blog series, we will work on preparing an aggregated data set that minimises the risk of disclosure. We hope to release this over the summer.\nThe analysis presented here used the following packages:\n\nFor data manipulation: dplyr, forcats, tidyr\nFor visualization and reporting: knitr, ggplot2\n\nThe code is available in the Rmarkdown file.\nThe banner photo was taken at useR! 2016 by Thomas Petzoldt, used with permission." + "objectID": "blog/2020/blacklivesmatter-statement/index.html", + "href": "blog/2020/blacklivesmatter-statement/index.html", + "title": "#BlackLivesMatter: A joint statement by Forwards and R-Ladies", + "section": "", + "text": "As organizations committed to broadening diversity and inclusion in our community, we stand with #BlackLivesMatter and join those who demand justice for systemic oppression. Pervasive racism negatively impacts the participation of Black people in society. The current events in the USA echo what has happened and continues to happen to minoritised people across the world. We are aggregating resources and are taking deliberate actions to amplify the voices of Black, Indigenous and People of Color in the R community now and moving forward.\nTo our community members who are suffering right now, we stand by you, we hear your voices, but we know that that is not enough to enact the change we need. The work of breaking systems of injustice is slow and hard, and we know that some of you are carrying more of the load than others. There are no words to make this easier." }, { - "objectID": "blog/2017/users-participation-in-the-r-community/index.html#footnotes", - "href": "blog/2017/users-participation-in-the-r-community/index.html#footnotes", - "title": "useRs Participation in the R Community", - "section": "Footnotes", - "text": "Footnotes\n\n\nSee our supplementary report: useR! 2016 participants and the R community: a multivariate analysis.↩︎\nR-Ladies Global Community and Vision, Gabriela de Queiroz, Cascadia R Conference, June 3, 2017, Portland, OR.↩︎" + "objectID": "blog/2020/blacklivesmatter-statement/index.html#a-message-from-forwards", + "href": "blog/2020/blacklivesmatter-statement/index.html#a-message-from-forwards", + "title": "#BlackLivesMatter: A joint statement by Forwards and R-Ladies", + "section": "A Message from Forwards", + "text": "A Message from Forwards\nForwards recognizes that Black people are often missing or overlooked in core activities of the R community. We acknowledge that many are frustrated by the slow progress or apparent lack of action. At a time when we are reminded that racial injustice pulls people down, it is our goal to create space for Black, Indigenous and People of Color to rise as R programmers and community leaders.\nWe work through small, but hopefully impactful actions, such as:\n\nHighlighting the work of people from underrepresented groups and sharing information about relevant events and opportunities on @R_Forwards Twitter.\nSupporting useR! conference organizers with the diversity scholarship program.\nRecommending people from underrepresented groups for roles such as conference speakers, committee members, session chairs, etc.\nSupporting the leadership team of AfricaR.\nReaching a diverse group with our workshops for women and girls and workshops in underserved regions (e.g. Cuba, Southern Africa).\n\nWe understand that there is much more that could be done to directly support and represent Black, Indigenous and People of Color and we are committed to play our part. We will continue to develop actions and long-term goals to improve intersectional representation in our taskforce and the wider R community." }, { - "objectID": "blog/2017/mapping-users/index.html", - "href": "blog/2017/mapping-users/index.html", - "title": "Mapping useRs", - "section": "", - "text": "Every year, hundreds of R programmers descend on a host city and spend three or four days sharing work, collaborating on projects and making new contacts - the useR! conference, this year held in Stanford, CA. useR! offers a wonderful opportunity to map a subset of the language’s most active users and the Women in R Task Force took this opportunity to survey attendees and find out their backgrounds, experiences and interests, in the hope that it will help us to get a better understanding of how to make the R community a more inclusive environment.\nOur survey received 455 responses, out of 899 attendees, and appears to represent the attendees pretty accurately.1 In this blog post, we’ll step through the attendees’ demographic background, how that represents the wider scientific and computing communities (and wider world), and propose recommendations for ways to bring these demographics towards parity." + "objectID": "blog/2020/blacklivesmatter-statement/index.html#a-message-from-r-ladies", + "href": "blog/2020/blacklivesmatter-statement/index.html#a-message-from-r-ladies", + "title": "#BlackLivesMatter: A joint statement by Forwards and R-Ladies", + "section": "A Message from R-Ladies", + "text": "A Message from R-Ladies\nWhile the R-Ladies mission is focused on improving gender diversity within the R community, we also recognize both the struggle that Black people face, and the compound effect of intersectionality when a member identifies with multiple underrepresented groups. R-Ladies Global makes a commitment to improve how the organization supports Black, Indigenous and People of Color through the following actions:\n\nWe will start and continue dialogue around concrete actions to promote social justice globally through dedicated channels in our Slack workspaces. As we engage, we commit to listening, empathizing, seeking to understand, and translating our conversations into action. We commit to making our community spaces places of not only safety for all our members, but of active work towards equity and justice.\nWe will incorporate into our website a dedicated page of resources and information regarding tangible actions we, as an organisation, and single individuals can take to support #BlackLivesMatter and other social justice movements.\nWe will improve ethnic and racial representation on the R-Ladies Global Team so voices from all intersectional minorities are better represented.\nWe will launch a number of programs to support our members (e.g. travel grants, book vouchers, educational subscriptions) through funds donated to R-Ladies, we will dedicate 50% of the funds towards community members with intersectional identities and half of that directed exclusively to Black members." }, { - "objectID": "blog/2017/mapping-users/index.html#summary", - "href": "blog/2017/mapping-users/index.html#summary", - "title": "Mapping useRs", - "section": "Summary", - "text": "Summary\nSurvey responses showed that attendees were largely male and white, with Latinx, Native American and people of African descent particularly under-represented. Attendees were almost all employed, and what’s more, employed in a permanent, full-time job. Attendence skewed heavily towards people in their late 20s and early to mid 30s, with men tending to be older than women, and attendees largely coming from the United States and almost exclusively from North American and Western European countries.\nOur recommendations are that, going forward, useR! conferences set aside tickets and funding for under-represented groups, and put resources into facilities such as feeding rooms and childcare that would benefit caregivers with small children, many of whom are women. Additionally, the Task Force itself will be refocusing its efforts and mission to emphasise the intersectional nature of marginalisation that women face, in line with the dispiriting results around race, employment and educational attainment. We will also be running further surveys to build up a better idea of the “ground truth” of the R community, and to track improvements and suggestions on an ongoing basis." + "objectID": "blog/2020/blacklivesmatter-statement/index.html#closing-statement", + "href": "blog/2020/blacklivesmatter-statement/index.html#closing-statement", + "title": "#BlackLivesMatter: A joint statement by Forwards and R-Ladies", + "section": "Closing statement", + "text": "Closing statement\nWe will work harder to listen to and amplify the voices of minoritized members of our respective communities worldwide. We are invested in the continuous work of breaking down systems of injustice, and in making room for those that are currently suffering in those systems to participate fully and occupy leading positions. We urge everyone in the R community to do the same.\nR Forwards Core Team: Heather Turner, Noa Tamir, Tatjana Kecojevic, Emily Dodwell, Kevin O’Brien, Julie Josse.\nR-Ladies Global: Claudia Vitolo, Erin LeDell, Hannah Frick, Laura Ación, Athanasia Monika Mowinckel, Yanina Bellini Saibene, Noa Tamir, Maëlle Salmon, Jennifer Thompson, Florencia D’Andrea, Patricia A. Loto, Saranjeet Kaur Bhogal, Christin Zasada, Nadejda Sero, Sheila Saia.\nR-Ladies chapter organizers (current and former) with others strongly involved in the R-Ladies and R communities: gwynn sturdevant, Paola Corrales, Paloma Rojas-Saunero, Riva Quiroga, Roxana Noelia Villafañe, Monica L. Alonso, Danielle Navarro, Mine Çetinkaya-Rundel, Sara Mortara, Genelle Denzin, Divya Seernani, Elisa Schneider, Kyla McConnel, Ana Laura Diedrichs, Liza Dosso, Mariel Lovatto, María Nanton, Ludmila Janda, Hazel Kavili, Ines Teacã, Lucía Rodríguez Planes, Andrea Sánchez-Tapia, Disha Patil, Ayanthi Gunawardana, Jan Strappa, Kaelen Medeiros, Vebashini Naidoo, Emily Dodwell, Julia Silge, Marcela Alfaro, Jenny Bryan, Lucy D’Agostino McGowan, Alison Hill, Andrea Gómez Vargas, Angela Li, Beatriz Milz, Haydée Svab, Tijana Blagojev, Katarina Kosmina, Jovana Savic." }, { - "objectID": "blog/2017/mapping-users/index.html#survey-results", - "href": "blog/2017/mapping-users/index.html#survey-results", - "title": "Mapping useRs", - "section": "Survey results", - "text": "Survey results\n\nGender and race\nThe gender breakdown of responses (n=453) showed that approximately 33% of attendees identified as women, with the majority of the remainder identifying as men and a small number identifying outside the gender binary.\nWhile the inclusion of women is not as bad as at other conferences, it’s also definitely lower than it could be given that there are many scientific fields - such as biology, which R is particularly commonly used in - where women outnumber men in terms of degree attainment.2 At the same time, some of this may be offset by the location and chosen topics for presentations, which were more focused on visualisation or computing than biostatistics.\nRace is more complicated, because there’s more variation in the answers - as intended! Both race and gender questions were offered as a free text field to avoid restricting respondents to false dichotomies. One side-effect, though, is that it’s hard to aggregate the data. What we can say, though, is:\n\n74% of respondents identified as White or Caucasian;\n16% fell within the US Federal guidelines for ‘Asian’, or identified directly as Asian;\n3% identified as Hispanic or Latinx;\n1% identified as people of African descent;\n0.5% identified as Native American or Pacific Islander;\n0.25% identified as Middle Eastern and\n3% identified as mixed-race.\n\nIn comparison, a survey of STEM workers in the United States found 6% were Black and 7% Hispanic3 4 - and the overall demographics of the United States point even more clearly to an under-representation of non-Asian minority groups.5 The response rate was somewhat lower on this question (n = 409), perhaps due to concerns about identifiability. Nonetheless, there’s clearly work to be done.\n\n\nLGBT\n5% of respondents identified as Lesbian, Gay, Bisexual or Transgender. How this maps to overall industry, academic and population trends is hard to identify, because the long history of persecution of LGBT individuals and the often confusing and ill-defined nature of identity means that the proportion of LGBT individuals is regularly under-reported. Attempts to control for that under-reporting have shown up to 19% of the U.S. population experience same-sex attraction,6 although more traditional methodologies suggest around 11%.7\nIt’s possible that the useR! survey is one of the surveys in which under-reporting is found - although 447 responses were received, which suggests people at least didn’t skip it - but it’s probably fair to say that such a sizeable difference in outcome is going to contain some genuine differences in population, as well as methodological variation.\nAdditionally, it is probable that the other demographics of LGBT attendees reflect the overall demographics of attendees, meaning that (for example) we would expect to find lesbians or bisexual women under-represented in that 5%.\n\n\nAge\nApproximating age (by subtracting the year of birth from 2016) shows the following:\n\nWomen trend younger than men at the conference, but the age distribution is similar across the two genders; 47% of respondents (n = 438) were born in the 1980s - in other words, were people in their late 20s to mid 30s. This lines up neatly with the education data (more on that later) and suggests that people in their early 20s and 40+ year olds are not finding the conference appealing - because there are other things to spend time on, because money is tighter, or for some other reason.\nThe women-being-younger element suggests that the rise in women attending (compared to 2015, where the proportion of women was only 19%) represents younger or newer members of the community attending, too.\n\n\nGeography\nThe R community is a highly international one, with developers in a wide range of countries. One of the things we were interested to discover is how this comes out in the attendee mix at useR!. Accordingly, we asked attendees which country they currently resided in.\nAltogether, R programmers from 34 nations attended useR!, but the overwhelming majority of respondents (71% of n = 443) live in the United States. In some ways this isn’t surprising - the cost of getting to Stanford increases the further away you are, and it’s expensive to start with! - and the rotation of the conference between continents each year means that many non-US R programmers are likely to simply attend the next European event. At the same time, it’s still somewhat disappointing for an event considered the “main” R conference, particularly with only ~20 attendees coming from Canada, a country bordering the U.S.\n\n\n\nEducation\nThe vast majority of attendees (>85%, of n = 451) had completed postgraduate degrees:\n\n\n\nHighest Qualification Completed\nWomen (%)\nMen (%)\n\n\n\n\nProfessional degree or certification\n1.2\n2.8\n\n\nDoctorate\n41.7\n45.7\n\n\nMasters degree\n42.9\n40.4\n\n\nUndergraduate degree\n13.7\n10.3\n\n\nHigh school/Secondary school or lower\n0.6\n0.7\n\n\n\nThis further suggests, on top of the data around age, that the conference is not attracting younger and more-early-career R programmers and researchers. Part of this may simply be that spending money on an R conference may be a lot easier to justify when you’re in full-time employment, or in a postgraduate degree with a stipend, than as an undergraduate or masters student; part of it is probably also that people without degrees, or without postgraduate degrees, earn less money and may come from poorer backgrounds, extending the problem.\nAt the same time, it is worth noting that the concept of research conferences as places to attend is not something particularly pushed on undergraduates, and so there is a component of awareness as well as finance. Finally, it may simply be that the conference is very academia-oriented, and so is particularly attractive to academics (and those familiar with academia) rather than R programmers without an academic background.\nAs the age data suggests, women tend to be slightly earlier on in the traditional academic career path.\n\n\nProfessional environment\nAlmost all of the attendees were employed, which (with the cost of the tickets) makes sense. More interestingly, a majority of the attendees (~57% of n = 444) were employed outside academia, primarily by private sector organisations. This is a strong indicator of what we’ve known anecdotally for a while - that R, a language originally designed and used in academia, is becoming more prevalent outside that context. At the same time, this may be a (somewhat) localised effect: while the language is increasingly popular, the technology industry centred on Silicon Valley is certainly an outlier in many respects for research overall.\n\nAnother interesting takeaway was that men are more likely to work in industry and permanent academic jobs than women - and women are far, far more likely to be students. Again, this isn’t surprising since it fits the pattern that women attending tend to be younger than men, and overall patterns that the tech industry (which is where one would expect the majority of privately-employed R programmers and scientists to work) has a known problem with employing and promoting women, as does academia.\nAlmost all attendees work full-time. It’s difficult to tell if this is due to the wider community largely being employed or engaged in full-time activities, or due to the cost of attendance diminishing the ability of community members in more economically fragile situations such as part-time work or unemployment to attend. Female attendees were less likely to work part-time, and far more likely to identify their status as unemployed (although the sample size is too small to really draw conclusions):\n\n\n\nEmployment Status\nWomen (%)\nMen (%)\n\n\n\n\nFull-time\n92.2\n94.3\n\n\nPart-time\n1.8\n4.3\n\n\nI am not currently employed\n6.0\n1.4\n\n\n\nThe proportion identifying as unemployed is greater than the proportion that previously identified as unemployed or retired, which could indicate that some students are categorising themselves as ‘not in employment’ when not presented with an option that reflects student-status.\n\n\nCaregiving\nApproximately a quarter of respondents answered “yes” to the question “are you a caregiver for children or adult dependents on a regular basis?” (n = 445). More men than women identified as caregivers. This either indicates that R programmers are a singularly socially enlightened population, or reflects wider sociological conditioning around caregiving which makes it easier for men to leave children at home with their partner (if applicable) than for women to do the same - resulting in a self-selection effect in which women with children are less likely to be able to attend (and so women who do attend are less likely to have children they care for).\nQualitative data suggests, unsurprisingly, the latter - in the free-text field for the survey, several (female) respondents mentioned the difficulty of persuading their (male) partners to handle childcare to allow them to attend conferences.\n\n\n\nCaregiving Status\nWomen (%)\nMen (%)\n\n\n\n\nNo\n78.3\n71.2\n\n\nYes\n21.7\n28.8" + "objectID": "blog/2019/the-state-of-r-in-africa/index.html#growth-of-the-r-ecosystem-in-africa", + "href": "blog/2019/the-state-of-r-in-africa/index.html#growth-of-the-r-ecosystem-in-africa", + "title": "The state of R in Africa", + "section": "Growth of the R ecosystem in Africa", + "text": "Growth of the R ecosystem in Africa\nOver the past 2 years, we have seen R transform from just an academic and health care research language to one of the major languages in the budding data science community in Africa. For a long time, data scientists and related disciplines have relied on R and many other packages to analyse data, however, the broader developer community didn’t fully understand its power in the tech industry. An effective model to enter the Africa developer ecosystem relies on a small group of enthusiasts creating a safe learning environment, documenting and sharing their learning experiences and slowly attracting interested learners. Africa R users group are using this model to introduce R as a language for data science by organising communities across different cities in Africa." }, { - "objectID": "blog/2017/mapping-users/index.html#recommendations", - "href": "blog/2017/mapping-users/index.html#recommendations", - "title": "Mapping useRs", - "section": "Recommendations", - "text": "Recommendations\n\nConference proposals\nThe survey data surfaces a lot of problems that can be tackled directly by future useR! conferences, and other conferences in the field too. In particular, it shows that while the gender breakdown of the conference is not as bad as we might fear, it’s still lagging behind the general population of the scientific fields R programming draws from, as well as the population as a whole. In addition, and in some ways more worryingly, attendees are overwhelmingly white, with Native Americans, Latinx people and people of African descent particularly under-represented.\nThese problems won’t be solved overnight, but there are several things the conference can do that would make attending a more viable and enjoyable prospect for under-represented groups. These include:\n\nA wider scholarship system. useR! 2016 featured scholarships, helping pay for things like plane tickets or hotels for people from marginalised backgrounds who wished to attend. The committee tasked with allotting the money did excellent work, but the money available was small. Expanding the scholarship fund in future conferences would let more under-represented R programmers attend, going a long way towards making a more representative conference.\nChildcare and feeding support. One of the things we saw in qualitative data, and something the quantitative data points to, is that the difficulties of juggling childcare is a blocker on attendance, particularly for women. Providing subsidised or free childcare at the conference itself (along with breastfeeding rooms), and incorporating childcare into the scholarship system, would help with this, and has been successfully done elsewhere.8\nStaggered ticket release. useR! 2016 sold out incredibly quickly, with all of the tickets gone within a day. This made it difficult for people to attend if they weren’t extremely on the ball and able to decide, on or before the first registration day, that they wanted to attend. By definition this hurts marginalised people because it hurts people who, for financial reasons, need to put some energy behind working out if they can attend. One solution worth considering is staggering the release of tickets over several days or weeks - perhaps with a waiting or notification list. This offers potential attendees multiple opportunities, reducing the penalty paid for not being ready to go on day 1.\nA more precise code of conduct. Following an open letter in 2015 the R Foundation adopted a resolution that any Foundation-affiliated conference have a Code of Conduct,9 which we applaud. What that code contains, however, in terms of restrictions, the amount of information given to attendees, and the enforcement mechanisms and their ease of use, is largely left up to the individual conference instance. This creates inconsistency and uncertainty for both attendees and conference organisers. Selecting a specific code of conduct, with a specific enforcement mechanism, along with training for enforcers, would solve for much of this, and give concerned attendees more certainty that the conference is a safe place to be.\n\n\n\nTask Force proposals\nThis survey has also helped to shape the goals of the Task Force on Women in the R Community. In particular, focusing in women, as a catchall, is not enough. Issues such as race, sexuality, disability and class intersect with gender and must also be considered if we are to build an R community that is more representative of the scientific/software communities and of society as a whole.\nAccordingly we are rebranding the Task Force as simply Forwards, so that we can consider the needs of other marginalised groups as part of our mission. Our primary focus will still be on women as there remains much work to do here and broadening participation of women was the motivation for setting up the task force. However many of the practical actions we can take, such as the proposals above, will also impact other marginalised groups and making this impact a formal part of our mission will help to ensure our actions do not only benefit white, highly educated women.\nAs an immediate consequence, we will be publishing an open call for participation, seeking more members for the group. We are particularly interested in talking to volunteers from non-White, LGBT, non-middle-class or early career backgrounds.\nRunning this survey has also served to reinforce that we have no fundamental ground truth here; it is hard to see what the backgrounds of those who try but fail to attend useR are, and their reasons for not going - it is hard to see what the demographics of R community members overall look like. Accordingly we will be running further surveys, adjusting several questions to factor in things we’ve learned from running this one, looking at the overall community and useR! attendees in a more nuanced way." + "objectID": "blog/2019/the-state-of-r-in-africa/index.html#evolution-of-chapters-and-representation", + "href": "blog/2019/the-state-of-r-in-africa/index.html#evolution-of-chapters-and-representation", + "title": "The state of R in Africa", + "section": "Evolution of chapters and representation", + "text": "Evolution of chapters and representation\nThe growth of technical talent in Africa positively correlates with the growth of communities around certain technologies/tools/languages. These communities are creating a long table to share opportunities on the continent. When we shift the spotlight to R in the Africa tech community we see an evolution in useR groups of not only academic researchers using R in their PhD or master’s degrees but also people using R at their workplaces or for their freelance projects. There is a unique representation in the Africa R community that shows how the useRs have created a safe space for equal active participation. Global communities like R Ladies and Women in Machine Learning and Data Science have given so many women in the community a platform to start R user groups in their localities. The support from these groups has contributed to the early success of R user groups as the safest places to start your data science career. \nSome of the chapters include Kampala,Lagos,Dar es salaam, Abidjan, Johannesburg,[DRC] (https://mobile.twitter.com/DrcUsers),Cotonou among others." }, { - "objectID": "blog/2017/mapping-users/index.html#notes", - "href": "blog/2017/mapping-users/index.html#notes", - "title": "Mapping useRs", - "section": "Notes", - "text": "Notes\nIf your company would like to sponsor diversity scholarships or childcare at useR! 2017, please contact the chair of the local organizing committee, Tobias Verbeke (%20tobias.verbeke at openanalytics dot eu).\nWe do not plan to release the raw survey data as many individuals can be uniquely identified from one or two demographic questions. We may release the data in an aggregated form once we have completed our full analysis (this post covers the first of three sections).\nThe analysis presented here used the following packages:\n\nFor data manipulation: dplyr, forcats, maptools, matrixStats, tidyr\nFor visualisaton and reporting: knitr, ggplot2, mapproj, RColorBrewer, rworldmap, scales\n\nThe code is available in the Rmarkdown file." + "objectID": "blog/2019/the-state-of-r-in-africa/index.html#events", + "href": "blog/2019/the-state-of-r-in-africa/index.html#events", + "title": "The state of R in Africa", + "section": "Events", + "text": "Events\nMonthly Meetups: These are the most popular events in the community. Groups of 10-50 useRs meet every month to learn and help each other with R related issues. They are usually supported by the local useR group in the area and are at the forefront of the growing popularity of data science in the local communities.\nSatRday: The R community in Johanessburg and Kampala have both hosted satRday events in April 2019 and May 2019 respectively. These events featured lightning talks and hands-on workshops for R users and were free. These have been the biggest R focused events on the continent for the year and the hope is they will spread to other regional hosts in the coming year." }, { - "objectID": "blog/2017/mapping-users/index.html#footnotes", - "href": "blog/2017/mapping-users/index.html#footnotes", - "title": "Mapping useRs", - "section": "Footnotes", - "text": "Footnotes\n\n\nSee our supplementary report Non-Responses in the UseR! 2016 Survey↩︎\nNational Science Foundation (2013) Women, Minorities, and Persons with Disabilities in Science and Engineering↩︎\nLandivar (2013) Disparities in STEM Employment by Sex, Race, and Hispanic Origin↩︎\nNative Americans are technically overrepresented, but given we’re talking about single digits of attendees here that probably isn’t meaningful - see CEOSE (2012) Biennial Report to Congress↩︎\nUnited States Census↩︎\nCoffman (2013) The Size of the LGBT Population and the Magnitude of Anti-Gay Sentiment are Substantially Underestimated↩︎\nGates (2011) http://williamsinstitute.law.ucla.edu/research/census-lgbt-demographics-studies/how-many-people-are-lesbian-gay-bisexual-and-transgender/↩︎\nBrown (2014) PyCon 2014: Community, community, community. Also, childcare.↩︎\nR Foundation (2015) https://www.r-project.org/behaviour.html↩︎" + "objectID": "blog/2019/the-state-of-r-in-africa/index.html#the-future", + "href": "blog/2019/the-state-of-r-in-africa/index.html#the-future", + "title": "The state of R in Africa", + "section": "The Future", + "text": "The Future\nR as a statistical programming language has a great value to the data science community on the continent and useRs are showing this value through their work, research and education. Most useR groups in Africa currently focus on developing material that shows the amazing facets of R, rendering it as an option on the table for potential clients and the community. We are starting to see R cross paths with other programming languages thus raising a need to create room for it in learning and early career choices through building communities, mentoring talent and eventually powering businesses. Follow AfricaR and individual chapters on their social media to view the most recent updates on events." }, { - "objectID": "blog/2017/emily-robinson-interview/index.html", - "href": "blog/2017/emily-robinson-interview/index.html", - "title": "Emily Robinson, from Social Scientist to Data Scientist", + "objectID": "blog/2018/r-in-latin-america/index.html", + "href": "blog/2018/r-in-latin-america/index.html", + "title": "R in Latin America", "section": "", - "text": "Maëlle Salmon, a Forwards collaborator, got the chance to interview Emily Robinson, who recently became a data analyst at Etsy. A very inspiring R-Lady!\n\nHi, Emily! Thanks for letting us interview you! You studied Decision Sciences at Rice University and then graduated from INSEAD with a Master’s degree in Management (specialization in Organizational Behavior). What are those fields? How do they help you today?\nDecision Sciences was an interdisciplinary major I actually created at Rice in my sophomore year based on Carnegie Mellon’s major. Before then I’d been planning to major in economics or psychology, but I found that neither really satisfied what I was looking for: to understand how people make decisions. So I decided to take the rarely used option at Rice to design my own curriculum with the input of many faculty members, and I created a course list that was a mix of economics, psychology, statistics, and philosophy.\nOrganizational Behavior is a pretty broad field, but essentially is the application of sociology and psychology applied to organizations/work. So people study everything from the effect of power on behavior to the benefits and pitfalls of multicultural teams to how social activists affect corporate political activity. I focused more on the micro (psychology) side and studied women in STEM fields.\nAll of the statistics courses I took have definitely helped. Also, the data science project process is actually quite similar to social sciences research: you come up with a question or a hypothesis, gather and clean the data, run an analysis, and communicate your findings.\nFinally, I think there’s often a place for knowledge about human and organizational behavior to come into the data science research process. I talked a lot in my interviews about how social sciences knowledge could be used in designing experiments; for example, the fact that giving people more choices actually makes them less likely to buy something, or that people from different countries use satisfaction scales differently (e.g. an American and a German may be equally satisfied with a product, but because of cultural reasons the German gives a lower score on a scale out of 10).\nYou then decided to become a data scientist instead. What motivated this decision? (Also, note we now assume you make decisions in a smarter way than most of us, given the name of your college major!)\nShort answer: I felt data science was where the most interesting questions, tools, and data were. I also believe that working as a data scientist/analyst offers a bigger possibility for broad impact than academia. While there’s definitely a lot of interesting and important research being done in academia, it’s a very long, slow process, with a lot of luck, and often times doesn’t reach anyone outside of the ivory tower. If anyone wants the longer story, please feel free to reach out to me on twitter/email.\nWhen did you first come in contact with R? Was it love at first sight? From which point did you feel enough at ease to be not only a R user, but also a R programmer?\nI was very lucky to do my undergraduate degree at Rice University, where at the time Hadley Wickham was a Statistics Professor. I only took one course with him, an Introduction to Statistics course, which didn’t involve R, but he had also designed later courses that were taught by his graduate students. At the time I didn’t realize how prominent in the R community he was, despite my brother Dave Robinson (then a PhD student at Princeton, now a data scientist at StackOverflow) shouting at me how cool it was that I was being taught by Hadley.\nBecause the courses were so well-designed and taught, I definitely fell in love with R at first sight. Despite its reputation as having a steep learning curve, I found it fairly straight forward to pick up (or maybe I’m just romanticizing it in my memories). That being said, I didn’t use it much outside of my statistics courses that required it, except to make a few plots for one of my research projects. It was in graduate school that I started to use R of my own volition. As I wrote about in one of my blog posts, I got so frustrated with using STATA, the language of choice for my graduate program, for certain class assignments that I switched to using R.\nI think this transition from being an R user to R programmer was also helped by some new tidyverse packages that came out in the last few years, especially dplyr. While the packages I initially learned, like reshape2 and plyr, were great, R has clearly advanced in the four years since I did most of my R courses.\nWhat is this program you’ve done for transitioning into your new career and how did you hear about it? How much can one learn in 12 weeks?\nMetis is a Data Science Bootcamp that helps people transition into careers as a Data Scientist/Analyst. I heard about it from my brother, who had spoken at Metis and gone to their career day, where students present their final projects to recruiters and data scientists. He had been really impressed by the quality of the students and their work, and so I looked into the program more. I found that it fit perfectly my background, as what I was missing was Python skills and Machine Learning knowledge. Metis is not meant to take you from 0 to 60; everyone who enters the program has some knowledge of statistics and programming, although their backgrounds still vary widely. In my cohort, we had people a few years out of college, one person with twenty years of marketing experience, and a few with PhDs in quantitative fields.\n Emily’s Metis cohort plus the two instructors (two people on the right)\nIn terms of what you can learn in 12 weeks, Metis is not meant to make you an expert in everything they cover. Rather, by giving you exposure to many topics and having you do projects around them, you get a good enough grounding so that you can continue learning on your own. It also gives you a portfolio of projects that you can host on your GitHub and talk about during interviews. The other big benefit is the career support from the Metis career team and from the extensive alumni network. You receive help in making a resume and prepping for interviews, but also in connecting you to people at the companies you’re interested in. For me it was 100% worth it. It was also a lot of fun and I met some great people!\nYou had to use Python at Metis: Which language do you use the most now? Could you use only Python?\nSince I just started my position, I’m not sure which language I’ll be using more. Etsy is pretty agnostic for which language its analysts use, and a lot of the work is done in SQL since we are working with such big datasets. If I had too, I could definitely use only Python, since I did use it so intensely for those few months. But I’m still definitely biased towards R and will probably be using that more.\nYou have just started a job at Etsy as a data scientist (congrats!). Could you tell us a little bit more about your job there? What kind of problems do you solve? How is the work organized between members of your team?\nThank you! My official title is actually Data Analyst and I’m on the analytics team; Data Scientists at Etsy are on the engineering (production) side and generally have PhDs in Computer Science/Machine Learning or similar backgrounds. While the analytics team sits together, we are embedded with other teams and serve as a sort of consultant, helping those teams improve how they use and analyze their data, run experiments, etc. For example, we have analysts working with marketing, accounting, seller services, etc.\nI’ll be working on search, which I’m very excited about since search is such a big part of the Etsy experience. Etsy actually just acquired BlackBird Technologies and their team to bring AI into their search, which should offer a lot of new opportunities. I’ll be working closely with another senior analyst and the broader search sciences team.\nThat all being said, Etsy does a great job with orientation and the first few weeks are dedicated to meeting people, reading analytics on-boarding materials, and getting my tech stack set up. So I haven’t heard anything yet about what specific projects I’ll be working on and won’t for a little while.\nWhat would you wish to have known sooner on your way to become a data scientist?\nDon’t be intimidated! It’s easy to feel like unless you have a PhD in Machine Learning and are an expert in Big Data that there are no roles for you. This isn’t helped by the fact that some companies’ job postings read like a wish list for a Data Scientist unicorn. But if you’ve been working on building your skills, you can find a position for you. You also DO NOT need to necessarily meet all of the job requirements; don’t be afraid to apply to a job where you’re just missing one of multiple criteria, or you have a year or two fewer years of experience than they mention.\nAnd as with almost every job, networking is critical. At some companies, there are thousands of people applying for each position, and having someone refer you can really help you get your foot in the door. Even more than that, talking to someone about the culture and day-to-day work in a company will really help you in your interview, because you’ll know more about what they’re looking for and if you’re a good fit.\nFinally, don’t be hung up on titles and only focus on positions where the title is “Data Scientist”. The work you’re doing is what’s important, and some data analysts are doing work that at other companies would be classified as a data scientist job. My title is a Data Analyst (as was Hilary Parker’s when she started out at Etsy), and while I’m not going to be doing deep learning projects anytime soon, I don’t think there’s going to be any shortage of interesting and challenging work.\nYou mention the importance of giving back to the open-source community on your blog, Hooked on Data. What are your plans with the blog and your programming in general? (Please keep writing on your blog!)\nOne big thing I want to do is host some in-person R tutorials for the R-Ladies NYC group. They had their kick-off meeting a few weeks ago, and many people expressed interest in an introduction to R tutorial and a more advanced one. While there are definitely some good resources online, my favorites are DataCamp for interactive tutorials and Hadley and Garrett’s new R for Data Science book, I do think it can sometimes be easier to learn in person. I tried to get more people in my graduate program (including professors!) to use R, so I’d love to help a group that already recognizes the value of R and is eager to learn.\nOther than that, I definitely want to keep blogging. I think a lot of my work at Etsy is going to be confidential, so I won’t be able to share that, but hopefully I’ll be able to talk about some cool side projects I’m doing or general principles I learned from my work. I’ve promised posts about making my first R package and my final Metis project, so I’d better get going on those!\nP.S. DataCamp has a few free courses, but if anyone wants to try unlimited access you can do so for free for two days with this link. There’s some really great courses, including one by Hadley and his sister Charlotte, and another by my brother!\nLast but not least, we were thrilled to learn you are a RCatLady although you don’t have a cat! Also you have a dog! Is she a good R-Dog?\n Emily’s R-Dog Abby\nShe is the best R-Dog. I’m very excited that Etsy is a dog-friendly office, and I plan to take her into the office sometime soon. I’m sure she’ll be very well-behaved; she spends most days sleeping on her bed or sitting under my mom’s desk at home right by her feet.\nOkay now we are very jealous! Thanks again Emily for talking with us, all the best for the future!\nContact Emily via her email address (robinson.es at gmail dot com), go read her blog, follow her on Twitter, Github, or LinkedIn.\nDisclaimer: The views expressed in this interview represent Emily’s own views and opinions, not necessarily those of Etsy.\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" + "text": "Following on from our post on R in Africa this next post in the series looks at the R community across Latin America." }, { - "objectID": "blog.html", - "href": "blog.html", - "title": "Blog", - "section": "", - "text": "Our blog is aggregated by R Weekly and R Bloggers.\n\n\n\n\n\n\n \n \n \n Order By\n Default\n \n Title\n \n \n Date - Oldest\n \n \n Date - Newest\n \n \n Author\n \n \n \n \n \n \n \n\n\n\n\n \n\n\n\n\nBlackLivesMatter: A joint statement by Forwards and R-Ladies\n\n\n\n\n\n\n\ncommunity\n\n\nnews\n\n\n\n\n#BlackLivesMatter: A joint statement by Forwards and R-Ladies\n\n\n\n\n\n\nJun 6, 2020\n\n\n\n\n\n\n \n\n\n\n\nSouthern Africa Project 2020\n\n\n\n\n\n\n\ncommunity\n\n\neducation\n\n\nsoftware\n\n\n\n\nReview of the R training and community events organized as part of the Forwards Southern Africa Project 2020, in South Africa, Eswatini and Botswana.\n\n\n\n\n\n\nMay 25, 2020\n\n\nHeather Turner\n\n\n\n\n\n\n \n\n\n\n\nRecap of R-Ladies Charlottesville Forwards Workshop\n\n\n\n\n\n\n\neducation\n\n\nsoftware\n\n\ncommunity\n\n\n\n\nLessons from R-Ladies Charlottesville Forwards Workshop\n\n\n\n\n\n\nNov 22, 2019\n\n\nAngela Li, Samantha Toet\n\n\n\n\n\n\n \n\n\n\n\nThe state of R in Africa\n\n\n\n\n\n\n\nnews\n\n\ncommunity\n\n\n\n\n2019 Round-up of initiatives in the R community across Africa.\n\n\n\n\n\n\nNov 15, 2019\n\n\nLorna Maria\n\n\n\n\n\n\n \n\n\n\n\nWorkshops for Women and Girls\n\n\n\n\n\n\n\neducation\n\n\nsoftware\n\n\ncommunity\n\n\n\n\nRound up of Forwards workshops supported by a grant from the R Consortium, to develop R package development skills among women and R coding skills among high school girls.\n\n\n\n\n\n\nSep 22, 2019\n\n\nForwards Teaching Team\n\n\n\n\n\n\n \n\n\n\n\nHavanaR Workshop 2018\n\n\n\n\n\n\n\nnews\n\n\ncommunity\n\n\neducation\n\n\n\n\nAnnouncement of joint >eR-Biostat and Forwards workshop in Havana, on visualisation methods and exploratory analysis of high dimensional and multivariate datasets in R.\n\n\n\n\n\n\nJul 7, 2018\n\n\nZiv Shkedy, Julie Josse\n\n\n\n\n\n\n \n\n\n\n\nR in Latin America\n\n\n\n\n\n\n\nnews\n\n\ncommunity\n\n\n\n\nRound-up of initiatives in the R community across Latin America.\n\n\n\n\n\n\nFeb 5, 2018\n\n\nAriel Levy, Fernando Mayer, Juan Pablo Marín Díaz, Riva Quiroga, Marcela Alfaro, Alejandro Reyes, Heather Turner\n\n\n\n\n\n\n \n\n\n\n\nR in Africa\n\n\n\n\n\n\n\nnews\n\n\ncommunity\n\n\n\n\nRound-up of initiatives in the R community across Africa.\n\n\n\n\n\n\nDec 1, 2017\n\n\nAndrew Collier, Anelda van der Walt, Ziv Shkedy, Theoni Photopoulou, Margareth Gfrerer, Heather Turner\n\n\n\n\n\n\n \n\n\n\n\nGirls Coding Workshop, Melbourne\n\n\n\n\n\n\n\neducation\n\n\nsoftware\n\n\ncommunity\n\n\ntraining\n\n\nteaching\n\n\n\n\nGirls Coding Workshop, Melbourne\n\n\n\n\n\n\nNov 20, 2017\n\n\nDi Cook\n\n\n\n\n\n\n \n\n\n\n\nuseRs Participation in the R Community\n\n\n\n\n\n\n\nanalysis\n\n\nuseR!\n\n\nsurvey\n\n\ncommunity\n\n\n\n\nCommunity Involvement of useRs\n\n\n\n\n\n\nJun 19, 2017\n\n\nStella Bollmann, Dianne Cook, Rudolf Debelak, Jasmine Dumas, John Fox, Julie Josse, Oliver Keyes, Carolin Strobl, Heather Turner”\n\n\n\n\n\n\n \n\n\n\n\nuseRs Relationship with R\n\n\n\n\n\n\n\nanalysis\n\n\nuseR!\n\n\nsurvey\n\n\nprogramming\n\n\n\n\nReport on programming section of useR! 2016 survey\n\n\n\n\n\n\nMar 11, 2017\n\n\nStella Bollmann, Dianne Cook, Rudolf Debelak, Jasmine Dumas, John Fox, Julie Josse, Oliver Keyes, Carolin Strobl, Heather Turner\n\n\n\n\n\n\n \n\n\n\n\nEmily Robinson, from Social Scientist to Data Scientist\n\n\n\n\n\n\n\ninterviews\n\n\ndata science\n\n\ncareers\n\n\n\n\n\n\n\n\n\n\n\nFeb 7, 2017\n\n\nMaëlle Salmon\n\n\n\n\n\n\n \n\n\n\n\nCall to Join Forwards\n\n\n\n\n\n\n\nnews\n\n\naction\n\n\n\n\nInviting New Members to join Forwards\n\n\n\n\n\n\nJan 13, 2017\n\n\n\n\n\n\n \n\n\n\n\nMapping useRs\n\n\n\n\n\nReport on demographics section of useR! 2016 survey\n\n\n\n\n\n\nJan 13, 2017\n\n\nStella Bollmann, Dianne Cook, Rudolf Debelak, Jasmine Dumas, John Fox, Julie Josse, Oliver Keyes, Carolin Strobl, Heather Turner\n\n\n\n\n\n\nNo matching items" + "objectID": "blog/2018/r-in-latin-america/index.html#conferences", + "href": "blog/2018/r-in-latin-america/index.html#conferences", + "title": "R in Latin America", + "section": "Conferences", + "text": "Conferences\nAs the use of R has grown in Latin America, there has been an increasing demand for local R conferences. The community has responded and a number of conferences are planned for the coming months.\n\nInternational Seminar on Statistics with R\nOne of the first to spot the demand was Luciane Alcoforado, a professor at the Fluminense Federal University (UFF) in Rio de Janeiro, Brazil. Realizing there was no large R event in Brazil, she set about coordinating the first International Seminar on Statistics with R (SER: Seminário Internacional de Estatística com R), which was held in Niterói in May 2016.\n Luciane Alcoforado, Coordinator of the first SER\nMore than 250 people attended this pioneering event, with attendance balanced across academia and industry. Encouraged by this success, the I SER organizers ran the event again in 2017, with an expanded program and similar numbers attending.\n Sean Kross presents remotely at the first SER\nA third edition, III SER, is now planned for May 22-24, 2018, to be hosted again by UFF in Niterói, Brazil. On the first day, 8 mini courses will be run, aimed at both practitioners and students. This year most of the international guests come from the USA and England. They include Jesse Mostipak, Becky Pattinson, Garreth Maccray, and Gabriela de Queiroz. These guests will present alongside invited speakers from the local region. There will also be thirty selected contributed talks and a poster session with awards for the best three of each. It’s a huge opportunity to get your research known. The last conference day will close with a tribute session to Prof. Djalma Pessoa who was a pioneer R user in Brazil.\nRegistration to III SER and the mini-courses is open now and the call for papers is open until March 23 2018.\n\n\nR Day\nA second event in Brazil, R Day, will take place at the Federal University of Paraná (UFPR), Curitiba, on May 22, 2018. The Statistics Department at UFPR was one of the first in Brazil to adopt R as the standard programming language for statistics teaching, in 2002. It was also the first institution to host a CRAN mirror in the country, and started the R-br mailing list in 2011, which now has more than 1000 subscribers.\nThe R Day is organized as a satellite event of the 63rd RBRAS meeting (Brazilian Region of the International Biometric Society), and is endorsed by the R Foundation to further develop the academic R community in Brazil. There will be three keynotes, 9 oral presentations, and 8 tutorials, aimed at both users and developers. The main goal is to be community-driven, so anyone can submit proposals for oral presentations and/or tutorials (only the three keynote speakers will be invited by the organizers).\nThe aim of R Day is to gather the vast R community in Brazil, by offering the possibility for users and developers to show their work and exchange experience on all sorts of R subjects. Proposals for oral presentations and tutorials are open until April 04. The registration is free and can be made until April 22.\nFor more information and updates, registration and proposal forms, checkout the R Day website, and follow us on Facebook and Twitter.\n R Day logo (left), Curitiba Botanical Garden (top right), and UFPR historical building (bottom right)\n\n\nsatRday Bogota\nThe first Latin American chapter of the one day conference series satRdays will take place in Bogota, Colombia in August 2018. The focus of the conference will be about tidy concepts applied to data visualization. It is organized by Datasketch, a Data Journalism Portal for Latin America.\nThe main goal of the conference is to create a common space for interaction among newbies and experts in R. Special interest will be given to works created by or for underrepresented communities and to showcase different solutions developed using R for the different elections that are happening in 2018 in different Latin American countries.\nThere are tentative plans for a workshop session the day before with hands-on tutorials about:\n\nData visualization and common mistakes.\nData structuring and preparation: PDFs, Databases and API’s.\n\nA website containing more details will be available soon.\n\n\nLatinR\nOn October 25, 2017, an announcement was made by Heather Turner on the RUG Organizers Slack: the R Foundation Conference Committee would like to see academic-focused R events in regions not currently covered by useR! In less than a week, a group of Latam R-Ladies were organizing their first conference-call to start thinking about how this challenge could be achieved. This quick response was not the result of mere chance, but the consequence of a year in which the R community — both RUG and R-Ladies groups — grew stronger in South America. By mid November everything was set-up: a name, a place, a date, and a motivated international organizing committee.\nLatinR 2018 will be held in Buenos Aires on September 4-5 within the 47th Argentinian Meeting of Informatics and Operational Research (JAIIO), which is organized by The Argentinian Informatics Society (SADIO). With a diverse and renowned Scientific Committee, this two-day event aims to bring together researchers, students, and R-enthusiasts from different backgrounds in order to strengthen the R community and make the impact that R is having in the region more visible, in both academic and non academic contexts.\nFor more information about oral presentations & poster submission, keynotes, and workshops, you can check out the LatinR website or follow us on Twitter and Facebook: @LatinR2018.\n\n\nConectaR 2019\nIn 2019, it is Costa Rica’s turn: ConectaR 2019 will take place in San José. The event has the endorsement of R Foundation and will be hosted at the University of Costa Rica (UCR). ConectaR has an organizing committee comprising members of academia (School of Statistics, Pure and Applied Mathematics Research Center (CIMPA)), public research centers (The Development Observatory, Bioversity International (CGIAR)) and industry (ixpantia). ConectaR will have two keynote speakers (yet to be confirmed) and will be receiving proposals for oral presentations and posters starting April 2018. In addition to that, there will be tutorials, invited talks, and a job fair. An attendance of over 150 people is expected, with the goal of building a community of R users in the Central American Region." }, { - "objectID": "about.html", - "href": "about.html", - "title": "About", - "section": "", - "text": "The task force was set up by the R Foundation in December 2015 to address the underrepresentation of women and rebranded in January 2017 to accommodate more under-represented groups such as LGBT, minority ethnic groups, and people with disabilities in the R community.\nThe members of the task force were invited to participate based on their interest in routing for specific under-represented groups and their contributions in the area of diversity and inclusion, to reflect different genders, ethnic groups, work contexts, career stages and aspects of the R project (e.g. CRAN and Bioconductor). The task force is organised as a core team plus a number of sub-teams that focus on particular tasks as outlined below:\n\nAccessibility: Working to improve access to R materials for people with low vision, blindness, hard of hearing, deaf, and other disabilities.\nCommunity: General outreach to help people from under-represented groups get into R and develop as useRs.\nConferences: Focusing on R Foundation conferences, liaising with organizers/program committee on policies and inclusion initiatives.\nOn-ramps: Creating paths for useRs to develop their skills and make contributions to the R/BioConductor package ecosystem.\nSocial Media: Posting to Twitter and/or Facebook, soliciting blog posts and publishing them, maintaining website.\nSurveys: Running and analysing community surveys, packaging up data and tools and maintaining the Data page.\nTeaching: Methodology, materials and workshops designed for under-represented groups.\n\nThe activities of the taskforce are recorded in the minutes of our bimonthly core team teleconferences and alternate monthly all team slackathons. We are open to new members joining one of our sub-teams. If interested, please contact rowforwards@gmail.com.\nThe task force is happy to engage with other individuals and organisations (such as R-Ladies) that are concerned about diversity and inclusion and actively seek outside collaboration on specific tasks." + "objectID": "blog/2018/r-in-latin-america/index.html#other-initiatives", + "href": "blog/2018/r-in-latin-america/index.html#other-initiatives", + "title": "R in Latin America", + "section": "Other Initiatives", + "text": "Other Initiatives\n\nR/Bioconductor Latin American Developers’ Workshop\nIn recent years, biology has seen a rise in the use of technologies that enable high-throughput, quantitative, data-rich profiling of cellular states. As a result, the field faces computational challenges to analyse such data. The R/Bioconductor project is an open source, open development software platform that provides tools to translate complex data sets into biological knowledge. An R/Bioconductor workshop will be held in Cuernavaca, Mexico on July 30 - Aug 3, 2018.\nThe workshop is aimed at students and researchers interested in the analysis of biological data. We encourage applications from diverse disciplines, including but not limited to biologists, bioinformaticians, data scientists, software engineers and programmers. The main goals of the workshop are:\n\nTeaching participants the principles of reproducible data science through the development of R/Bioconductor packages.\nTurning bioinformatic software users into bioinformatic software developers.\nFostering the exchange of expertise and establishing multidisciplinary collaborations.\nCreating a community of Latin American scientists committed to the development of software and computational pipelines for biological data analysis.\nHelping to train bioinformatics instructors that can continue to grow in their local communities.\n\nThis workshop is part of a long-term project to create a community of developers from Latin America. We hope to hold regular meetings in the future (similar to BioC, EuroBioc and BioCAsia) where attendees present their own software contributions.\nA website containing more details will be available soon.\n\n\nLocal groups\nBeyond conferences and workshops, local groups provide a venue for R users to meet more regularly. Jumping Rivers provide a user group directory, which also covers R-Ladies groups, however as R-Ladies are expanding rapidly it is worth checking the R-Ladies Starter Kit for the latest status.\nRecently members of the RUG and R-Ladies groups in Bogota, Columbia collaborated on a striking intervention about feminicides in Colombia using plots created in R. Read more on their initiative in this report (warning: readers may find the content distressing). This is an example of how local groups can work together on wider issues as well as providing networking and development opportunities for their members.\n\n\nMaking Connections\nPart of building the community in Latin America is making connections between disconnected groups. If you think we have missed something, or you would like to be involved in plans for future events in the region, let us know in the comments or contact us on email (rowforwards at gmail dot com) or Twitter.\nBanner image shows the poster session at I SER." }, { - "objectID": "about.html#background", - "href": "about.html#background", - "title": "About", + "objectID": "blog/2017/users-relationship-with-r/index.html", + "href": "blog/2017/users-relationship-with-r/index.html", + "title": "useRs Relationship with R", "section": "", - "text": "The task force was set up by the R Foundation in December 2015 to address the underrepresentation of women and rebranded in January 2017 to accommodate more under-represented groups such as LGBT, minority ethnic groups, and people with disabilities in the R community.\nThe members of the task force were invited to participate based on their interest in routing for specific under-represented groups and their contributions in the area of diversity and inclusion, to reflect different genders, ethnic groups, work contexts, career stages and aspects of the R project (e.g. CRAN and Bioconductor). The task force is organised as a core team plus a number of sub-teams that focus on particular tasks as outlined below:\n\nAccessibility: Working to improve access to R materials for people with low vision, blindness, hard of hearing, deaf, and other disabilities.\nCommunity: General outreach to help people from under-represented groups get into R and develop as useRs.\nConferences: Focusing on R Foundation conferences, liaising with organizers/program committee on policies and inclusion initiatives.\nOn-ramps: Creating paths for useRs to develop their skills and make contributions to the R/BioConductor package ecosystem.\nSocial Media: Posting to Twitter and/or Facebook, soliciting blog posts and publishing them, maintaining website.\nSurveys: Running and analysing community surveys, packaging up data and tools and maintaining the Data page.\nTeaching: Methodology, materials and workshops designed for under-represented groups.\n\nThe activities of the taskforce are recorded in the minutes of our bimonthly core team teleconferences and alternate monthly all team slackathons. We are open to new members joining one of our sub-teams. If interested, please contact rowforwards@gmail.com.\nThe task force is happy to engage with other individuals and organisations (such as R-Ladies) that are concerned about diversity and inclusion and actively seek outside collaboration on specific tasks." + "text": "In our first post on the useR! 2016 survey we discussed the responses from the demographic section, finding in particular that:\nWe now turn to look at useRs relationship with R: what experience do they have in using R and what do they think of R?" }, { - "objectID": "about.html#core-members", - "href": "about.html#core-members", - "title": "About", - "section": "Core Members", - "text": "Core Members\nHeather Turner - Chair and ‘On-ramps’ team leader. Heather is a Research Software Engineering Fellow in the Statistics department at the University of Warwick and is on the board of the R Foundation. (LinkedIn/Mastodon/ GitHub)\ngwynn gebeyehu - Administrator and ‘Accessibility’ team leader. gwynn completed a post-doc at Harvard Business School and co-founded of the Harvard Data Science Initiative R User Group. (Mastodon)/GitHub)\nJonathan Godfrey - ‘Accessibility’ team leader. Jonathan was the first totally blind person in the world to gain employment as a Lecturer in Statistics (Massey University, NZ). (Twitter/GitHub)\nKevin O’Brien - ‘Community’ team leader. Kevin is a data scientist working for a forestry company, modelling forestry resources, as well as one of the main organizers of Dublin R. (LinkedIn/Twitter/GitHub)\nElla Kaye - ‘Community’ team leader. Ella is a statistician and R enthusiast. She’s a founding member of RainbowR and a previous co-organiser of the Oxford R User Group. (LinkedIn/Mastodon/GitHub)\nYanina Bellini Saibene - ‘Conferences’ team leader. Yanina is a professor at national universities in Argentina and Uruguay and a researcher who applies data science to the agricultural sector. She is co-founder of MetaDocencia, part of the R-Ladies Global Team, co-founder and chair of LatinR, chair of useR! 2021, chair of the 49 & 50 JAIIO, and chair of the AgroInformatics Congress. (LinkedIn/Twitter/GitHub)\nNoa Tamir - ‘Conferences’ team leader (on leave). Noa is a Data Science Manager, an organizer of the R-Ladies Berlin and Women in Machine Learning and Data Science Berlin Meetups, and has recently organized the satRday Berlin 2019 conference. (LinkedIn/Twitter/GitHub)\nSaranjeet Kaur Bhogal - ‘On-ramps’ team leader. Saranjeet volunteers for the R-Ladies Global Team. She is a Statistician by training and likes to work for open source and open science. (LinkedIn/Twitter/GitHub)\nTatjana Kecojevic - ‘Surveys’ team leader. Tanja is a statistician, instructor and consultant. She is the founder of Sister Analyst, an NGO devoted to empowering women and other under-represented groups, in the field of data literacy and science. Tanja is also the founder and co-organiser of the R-Ladies Manchester and Belgrade chapters. Her enthusiasm for data science is matched by her commitment to inclusivity. Data skills should be accessible to anyone with a desire to discover. (LinkedIn/Twitter/GitHub)\nAndrea Sánchez-Tapia - ‘Surveys’ team leader. Andrea is a computational biologist, working with biodiversity informatics and open and reproducible workflows in ecology. She teaches R and other computational skills in academic and non-academic environments, and co-organizes R-Ladies Rio de Janeiro. (Twitter/GitHub)\nAnna Vasylytsya - ‘Surveys’ team leader. (LinkedIn/GitHub)\nMine Çetinkaya-Rundel - ‘Teaching’ team leader. Mine is a Professor at Duke University and Data Scientist & Professional Educator at RStudio. (LinkedIn/Twitter/GitHub)\nEmma Rand - ‘Teaching’ team leader. Emma is a Senior Lecturer (Associate Professor) at the University of York, UK and teaches reproducible data analysis to bioscientists in her institution and with the Royal Society of Biology and the Biochemical Society. (LinkedIn/Twitter/GitHub)" + "objectID": "blog/2017/users-relationship-with-r/index.html#summary", + "href": "blog/2017/users-relationship-with-r/index.html#summary", + "title": "useRs Relationship with R", + "section": "Summary", + "text": "Summary\nuseR! attendees have generally been using R for many years and often have prior programming experience. Women tend to have less experience and a lower involvement in package development, though this can be attributed to a lower age distribution.\nWomen are less likely to use R for recreation, but are just as likely as men to consider writing R fun. useR! attendees have a generally positive view of R and would recommend it to friends and colleagues for statistical analysis.\nWe recommend teaching R to newcomers in a way that focuses on data science and does not assume a programming background. Mentors and managers should recognize that people from under-represented groups may need additional support to fill in gaps in their programming knowledge. To encourage people from under-represented groups to develop as R programmers and contribute to the community, we recommend promoting opportunities and activities that are paid and/or help to advance their careers." }, { - "objectID": "about.html#sub-team-members", - "href": "about.html#sub-team-members", - "title": "About", - "section": "Sub Team Members", - "text": "Sub Team Members\nZane Dax - ‘Accessibility’ team member. (Twitter/GitHub)\nLiz Hare - ‘Accessibility’ team member. (LinkedIn/Mastodon/GitHub)\nFlorencia Mangini - ‘Accessibility’ team member. (Twitter/GitHub)\nBecca Wilson - ‘Accessibility’ team member. (LinkedIn/Twitter)\nTania Allard - ‘Community’ team member. (LinkedIn/GitHub)\nDamiano Cerasuolo - ‘Community’ team member. (LinkedIn/Twitter/GitHub)\nJoslynn Lee - ‘Community’ team member. (LinkedIn/Twitter/GitHub)\nSamantha Toet - ‘Community’ team member. (LinkedIn/Twitter/GitHub)\nJulie Josse - ‘Conferences’ team member. (LinkedIn/Twitter/GitHub)\nImke Mayer - ‘Conferences’ team member. (LinkedIn/Twitter/GitHub)\nMiljenka Vuko - ‘Conferences’ team member. (LinkedIn/Twitter/GitHub)\nJyoti Bhogal - ‘On-ramps’ team member. (LinkedIn/Twitter/GitHub)\nMichael Chirico - ‘On-ramps’ team member. (Twitter/GitHub)\nMaya Gans - ‘On-ramps’ team member. (Twitter/GitHub)\nMichael Lawrence - ‘On-ramps’ team member. (LinkedIn/Twitter/GitHub)\nPavitra Chakravarty - ‘Surveys’ team member. (Twitter/GitHub)\nPaola Corrales - ‘Surveys’ team member. (Twitter/GitHub)\nNujcharee Haswell - ‘Surveys’ team member. (LinkedIn/Twitter/GitHub)\nClaudia Huaylla - ‘Surveys’ team member. (Twitter/GitHub)\nDi Cook - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)\nEmily Dodwell - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)\nIsabella Gollini - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)\nRitwik Mitra - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)\nMaria Prokofieva - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)\nJoyce Robbins - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)" + "objectID": "blog/2017/users-relationship-with-r/index.html#survey-results", + "href": "blog/2017/users-relationship-with-r/index.html#survey-results", + "title": "useRs Relationship with R", + "section": "Survey results", + "text": "Survey results\n\nProgramming experience\nWe first asked attendees how long they had been using R for. Unsurprisingly for attendees of a conference all about R, the respondents tend to be rather experienced, with more than half (57%, 251 of 442) using R for at least 5 years. Nonetheless, the conference does attract people new to R, with a small number having less than 6 months experience. A greater proportion of women than men have fewer than two years experience (24%, 39 of 164 vs 12%, 34 of 276) which correlates with the younger age distribution we noted in our first post. The following plot shows the percentages within each experience category for each gender:\n\n66% of women (109 of 165) said they had programming experience before learning to use R, compared with 82% of men (227 of 276). Since women tend to be younger, this could be due to increasing use of R in teaching, particularly on undergraduate courses. Thus younger people generally are less likely to have used other languages for data analysis such as SAS, Stata, S-plus, Genstat, etc. However it could indicate a different background of women vs. men, in particular they may be less likely to have any formal training in computer science, where they might have been taught C/C++, Java etc before learning R.\nWe also asked about how people use the language. Respondents were asked to confirm that any or all of the following statements applied to them:\n\n“I use functions from existing R packages to analyze data”\n“I write R code designed to make my work easier, such as loops or conditionals or functions”\n“I write R functions for use by myself or my collaborators”\n“I contribute to R packages (on CRAN or elsewhere)”\n“I have written my own R package”\n“I have written my own R package and released it on CRAN or Bioconductor (or shared it on GitHub, R-Forge or similar platforms)”\n\nAs might be expected given the length of time useR! attendees have been using R, their use is generally quite advanced with the vast majority using techniques to control the flow of their code (86%, 392 of 458) or writing custom R functions (85%, 389 of 458). More than half have written their own package(s) (52%, 238 of 458) and a third have publicly released a package (34%, 155 of 458).\nReflecting the distribution of length of R programming experience, the proportion of women using advanced programming techniques is slightly lower than men and when it comes to package development the proportion is lower still:\n\nThe final question we asked regarding use of R was whether the attendees use R primarily for work, recreation or both. The results were significantly different for men and women, only 22% of women (35 of 162) use R for both work and recreation compared to 45% of men (147 of 275); the few people that use R for recreation only were all men. Although factors such as age and programming experience may come into play here, it is likely that social expectations of women are also a factor. For example, although responsibility for cooking, childcare and housework is shared more evenly among working couples, in different sex couples women often shoulder a greater responsibility1. With reduced leisure time, women may be less willing to use R just for fun, or may feel less able to do so, due to expectations of their family and friends about how they should spend their free time.\n\nOverall, this paints a picture of useR! attendees as a population of mostly long-term R programmers often writing code for more than their individual use - which makes sense. As we discussed in our first post, conferences are expensive in terms of both time and money, so a conference on R is most viable for people that use R substantially in their work and hence can justify the cost to their employers. As the main conference organised by the R Foundation, useR! is particularly attractive to dedicated contributors to the R project, indeed talks and posters should present a contribution which will often be a new package or contribution to a package. This goes some way to explaining some of the inequalities in attendee demographics; we know from separate research (albeit using a rather crude metric) that CRAN maintainers, for example, are mostly not women.2\nWe have seen that the women that do attend useR! tend to be younger and less experienced. We have not explored the programming experience of other under-represented groups, for example with regard to ethnicity or sexual orientation, as the numbers in the sample are much lower, prohibiting reliable statistical conclusions and creating issues with identifiability. It is possible that, like women, members of other under-represented groups are also less likely to use R for recreation, as they will tend to have less time or money than is the norm.3 This indicates a barrier to women and other under-represented groups transitioning from useRs to developeRs: package authorship and maintenance, and dedication to an open source community, is largely uncompensated.\n\n\nOpinions about R\nThe second part of our section on R programming asked respondents for their opinions on R. On these questions there were no significant differences between the responses from men and women, so we present the results for all respondents, including non-binary individuals and those that did not declare their gender.\nWe first asked respondents how strongly they agreed or disagreed with the following statements:\n\nwriting R is fun\nwriting R is considered cool or interesting by my peers\nwriting R is a monotonous task\nwriting R is difficult\n\nThe results are presented below:\n\nWe see that respondents overwhelmingly agree that writing R is fun, so even those people that use R primarily for work enjoy doing so. The view of their peers is slightly less positive, with 12% (51 of 438) stating that writing R is not considered cool or interesting by their peers and 15% having no opinion on this (65 of 438). Even among those who agreed with the second statement, the proportion that strongly agreed is lower compared to the first statement. So although the overall picture is positive, there is a sizable group for which writing R is not encouraged by their peers, which could affect their motivation to contribute, particularly outside of work.\nThe majority (61%, 269 of 438) disagree with the statement that writing R is difficult. Those that agreed with this statement are spread across the experience levels, so some may have been expressing a general opinion about R programming rather than a personal one, necessarily. The disagreement is stronger (80%, 349 of 438) against the statement that writing R is a monotonous task, so while writing R may occasionally be difficult most useR! attendees find it challenging and interesting.\nThe generally positive view of R among useR! attendees is not so surprising, after all most will have chosen to attend the conference, or if it was required by their work they have expressed an interest in R by applying for that job or choosing to use R at work in the first place. Nonetheless, the positive view is a benefit to the community as useRs encourage people to take up R and contribute more to the R project, with many useRs being in a position to teach R, mentor junior colleagues/students or contribute to community events such as R user groups or R-ladies.\n91% (418 of 439) said that they would recommend R to friends and colleagues. The reasons some people would not recommend R include a steep learning curve, too many idiosyncrasies, poor performance and that it encourages bad programming practice. Some simply said they would recommend other software over R or they may recommend R, depending on why their friend or colleague wanted to learn a programming language.\nWhen asked to pick a single reason for recommending R, nearly 40% (160 of 425) said it was good for statistical analysis. R has long been described as the lingua franca of statistics or data science, so this makes sense. The next biggest reason was that it was good for reproducible research, indicating the increasing importance that has been put on this topic in recent years. Other important features are the package ecosystem, strength at visualization and the fact that it is free and open source." }, { - "objectID": "about.html#previous-members", - "href": "about.html#previous-members", - "title": "About", - "section": "Previous Members", - "text": "Previous Members\nRichard Ngamita Lorna Maria Aine\nStella Bollman\nJenny Bryan\nNic Crane\nRudolf Debelak\nJohn Fox\nJasmine Dumas\nAndrea Foulkes\nGina Griffin\nMadlene Hamilton\nZhian N. Kamvar\nLiz Kellogg\nOs Keyes\nAngela Li\nGina Merchant\nDavid Meza\nIleena Mitra\nJesse Mostipak\nShakirah Nakalungi\nWenfeng Qin\nAugustina Ragwitz\nMaëlle Salmon\nDorris Scott\nTracy Shen\nDavid Smith\nCarolin Strobl\nCharlotte Wickham\nHadley Wickham\nYizhe Xu" + "objectID": "blog/2017/users-relationship-with-r/index.html#moving-forward", + "href": "blog/2017/users-relationship-with-r/index.html#moving-forward", + "title": "useRs Relationship with R", + "section": "Moving Forward", + "text": "Moving Forward\n\nOutreach to under-represented groups\nAs the R community seeks to be more inclusive of under-represented groups we need to be aware that individuals from these groups are less likely to have a programming background and may have less freedom to spend time on unpaid and recreational contributions. Given R’s strength as a tool for statistical analysis, introductions to R should focus on this rather than the nuts and bolts of the language, as a general rule. More experienced R programmers from under-represented groups may need additional support to transition to developeRs – even when writing packages in pure R, concepts such as version control and object-oriented programming may be new and of course interfacing with other languages such as C++ is a further stretch. We should seek to promote opportunities to under-represented groups that are paid and/or will benefit their career, e.g. Google Summer of Code projects, useR! diversity scholarships, professional development via R-ladies groups, developing a package with rOpenSci, publishing in The R Journal and so on.\n\n\nTaskforce initiatives\nFollowing our recent call to join Forwards we have set up a number of sub-teams to support women and other under-represented groups in the R community. In particular the teaching team will focus on more inclusive pedagogy, such as using examples to engage a wider demographic, and running workshops for women and girls. We have also set up a community team, to look at ways to reach out to under-represented groups and an on-ramps team to look at ways to help useRs transition to developeRs. These are all new initiatives, but we hope to get some projects off the ground in all these areas in the coming year. Anyone wishing to get involved can contact us at rowforwards at gmail dot com.\n\n\nFurther research\nSome interesting questions for further research on useRs relationship with R include:\n\nWhat programming experience do people have before using R? For example, what languages did people learn before R?\nWhy do people write packages but not publicly release them? For example, are the packages for their own use (work/recreation), for internal company use, or are the packages in development? One respondent commented that their employer prohibited releasing packages on CRAN; how widespread is this?\nWhat are the pros and cons of using R? Several respondents commented that R has many benefits but also some drawbacks and richer data could be collected on this topic." }, { - "objectID": "blog/2017/call-to-join-forwards/index.html", - "href": "blog/2017/call-to-join-forwards/index.html", - "title": "Call to Join Forwards", - "section": "", - "text": "Forwards, the R Foundation taskforce on women and other under-represented groups, is seeking to address issues affecting under-represented groups in general as it works to broaden the participation of women in the R community.\nIn order to adequately address such issues, we would like to widen the diversity of the taskforce itself. Accordingly, we are inviting people who are part of under-represented groups - be they groups identified by race, gender, sexuality, class or disability - to join us.\nThe taskforce has teleconferences once every two months, although as the taskforce is spread globally it isn’t possible for all members to attend every time. Therefore online communication is also important and there are occasional meetings within subteams. Subteams work on specific tasks, such as data collection and analysis, social media, or working on recommendations for R Foundation supported activities.\nTo express your interest or ask for further information, contact us at rowforwards at gmail dot com by 31 January 2017.\nCredit: Banner image by #WOCinTech Chat.\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" + "objectID": "blog/2017/users-relationship-with-r/index.html#notes", + "href": "blog/2017/users-relationship-with-r/index.html#notes", + "title": "useRs Relationship with R", + "section": "Notes", + "text": "Notes\nWe do not plan to release the raw survey data as many individuals can be uniquely identified from one or two demographic questions. We may release the data in an aggregated form once we have completed our full analysis (this post covers the second of three sections).\nThe analysis presented here used the following packages:\n\nFor data manipulation: dplyr, forcats, purrr, tidyr\nFor visualization and reporting: knitr, ggplot2, likert\n\nThe code is available in the Rmarkdown file.\nThe banner image was based on the plotHeart function written by Sandy Kawano for Valentine’s Day, based on this answer to a Stackoverflow post." }, { - "objectID": "blog/2017/girls-coding-workshop-melbourne/index.html", - "href": "blog/2017/girls-coding-workshop-melbourne/index.html", - "title": "Girls Coding Workshop, Melbourne", - "section": "", - "text": "The first girls R coding workshop was held at the Kathleen Symes library in Melbourne, Nov Oct 28, 2017. The girls learned about tidy data concepts, wrangling data tools, and built a shiny app to explore standardised test data from the 2015 OECD Programme for International Student Achievement. One of the apps developed can be viewed at https://t.co/zlw3HGzOaR.\nAnd we had lamingtons, upside down R cupcakes (R downunder) for morning tea, and pizzas for lunch.\n \nKeep an eye on https://forwards.github.io/edu/ for announcements about more workshops.\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" + "objectID": "blog/2017/users-relationship-with-r/index.html#footnotes", + "href": "blog/2017/users-relationship-with-r/index.html#footnotes", + "title": "useRs Relationship with R", + "section": "Footnotes", + "text": "Footnotes\n\n\nhttps://www.familiesandwork.org/downloads/modern-families.pdf↩︎\nhttps://forwards.github.io/data/#maintainer_gender_2016↩︎\nFor example, average earnings in the US are lower for many ethnic minorities in general and in science and engineering occupations in particular, including computer and information science specifically (https://www.nsf.gov/statistics/2017/nsf17310/static/data/tab9-17.pdf). The American Association of University Women report that gay and bisexual men tend to be paid less than similarly qualified heterosexual men; while trans women (who have transitioned from male to female) experience a drop in pay. They also report that transgender people frequently face harassment and discrimination; this may affect their motivation for voluntary contribution (http://www.aauw.org/resource/the-simple-truth-about-the-gender-pay-gap/).↩︎" }, { "objectID": "blog/2017/r-in-africa/index.html", @@ -427,332 +385,360 @@ "text": "Other activities\nHere we have focused on some of the more recent initiatives, but of course there are many other groups encouraging the use of R in Africa. For example, several general R User Groups have been established; many are listed on the Data Science Africa web site and a few more are listed on the R User Groups listing hosted by jumping rivers. On the education side, the centres of the African Institute of Mathematical Sciences (AIMS) often use R in their courses and workshops. In particular AIMS Tanzania is a partner in the Africa Data Initiative that developed R-Instat a front-end to R designed to make R more accessible for students. Going beyond the classroom, BeST (Bespoke eStyle Statistical Training for Africa and South Asia) assist in upskilling scientists working in agricultural development via online courses in R. If you are aware of other such initiatives, feel free to share them in the comments!" }, { - "objectID": "blog/2017/users-relationship-with-r/index.html", - "href": "blog/2017/users-relationship-with-r/index.html", - "title": "useRs Relationship with R", + "objectID": "blog/2017/girls-coding-workshop-melbourne/index.html", + "href": "blog/2017/girls-coding-workshop-melbourne/index.html", + "title": "Girls Coding Workshop, Melbourne", "section": "", - "text": "In our first post on the useR! 2016 survey we discussed the responses from the demographic section, finding in particular that:\nWe now turn to look at useRs relationship with R: what experience do they have in using R and what do they think of R?" + "text": "The first girls R coding workshop was held at the Kathleen Symes library in Melbourne, Nov Oct 28, 2017. The girls learned about tidy data concepts, wrangling data tools, and built a shiny app to explore standardised test data from the 2015 OECD Programme for International Student Achievement. One of the apps developed can be viewed at https://t.co/zlw3HGzOaR.\nAnd we had lamingtons, upside down R cupcakes (R downunder) for morning tea, and pizzas for lunch.\n \nKeep an eye on https://forwards.github.io/edu/ for announcements about more workshops.\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" }, { - "objectID": "blog/2017/users-relationship-with-r/index.html#summary", - "href": "blog/2017/users-relationship-with-r/index.html#summary", - "title": "useRs Relationship with R", - "section": "Summary", - "text": "Summary\nuseR! attendees have generally been using R for many years and often have prior programming experience. Women tend to have less experience and a lower involvement in package development, though this can be attributed to a lower age distribution.\nWomen are less likely to use R for recreation, but are just as likely as men to consider writing R fun. useR! attendees have a generally positive view of R and would recommend it to friends and colleagues for statistical analysis.\nWe recommend teaching R to newcomers in a way that focuses on data science and does not assume a programming background. Mentors and managers should recognize that people from under-represented groups may need additional support to fill in gaps in their programming knowledge. To encourage people from under-represented groups to develop as R programmers and contribute to the community, we recommend promoting opportunities and activities that are paid and/or help to advance their careers." + "objectID": "blog/2017/call-to-join-forwards/index.html", + "href": "blog/2017/call-to-join-forwards/index.html", + "title": "Call to Join Forwards", + "section": "", + "text": "Forwards, the R Foundation taskforce on women and other under-represented groups, is seeking to address issues affecting under-represented groups in general as it works to broaden the participation of women in the R community.\nIn order to adequately address such issues, we would like to widen the diversity of the taskforce itself. Accordingly, we are inviting people who are part of under-represented groups - be they groups identified by race, gender, sexuality, class or disability - to join us.\nThe taskforce has teleconferences once every two months, although as the taskforce is spread globally it isn’t possible for all members to attend every time. Therefore online communication is also important and there are occasional meetings within subteams. Subteams work on specific tasks, such as data collection and analysis, social media, or working on recommendations for R Foundation supported activities.\nTo express your interest or ask for further information, contact us at rowforwards at gmail dot com by 31 January 2017.\nCredit: Banner image by #WOCinTech Chat.\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" }, { - "objectID": "blog/2017/users-relationship-with-r/index.html#survey-results", - "href": "blog/2017/users-relationship-with-r/index.html#survey-results", - "title": "useRs Relationship with R", - "section": "Survey results", - "text": "Survey results\n\nProgramming experience\nWe first asked attendees how long they had been using R for. Unsurprisingly for attendees of a conference all about R, the respondents tend to be rather experienced, with more than half (57%, 251 of 442) using R for at least 5 years. Nonetheless, the conference does attract people new to R, with a small number having less than 6 months experience. A greater proportion of women than men have fewer than two years experience (24%, 39 of 164 vs 12%, 34 of 276) which correlates with the younger age distribution we noted in our first post. The following plot shows the percentages within each experience category for each gender:\n\n66% of women (109 of 165) said they had programming experience before learning to use R, compared with 82% of men (227 of 276). Since women tend to be younger, this could be due to increasing use of R in teaching, particularly on undergraduate courses. Thus younger people generally are less likely to have used other languages for data analysis such as SAS, Stata, S-plus, Genstat, etc. However it could indicate a different background of women vs. men, in particular they may be less likely to have any formal training in computer science, where they might have been taught C/C++, Java etc before learning R.\nWe also asked about how people use the language. Respondents were asked to confirm that any or all of the following statements applied to them:\n\n“I use functions from existing R packages to analyze data”\n“I write R code designed to make my work easier, such as loops or conditionals or functions”\n“I write R functions for use by myself or my collaborators”\n“I contribute to R packages (on CRAN or elsewhere)”\n“I have written my own R package”\n“I have written my own R package and released it on CRAN or Bioconductor (or shared it on GitHub, R-Forge or similar platforms)”\n\nAs might be expected given the length of time useR! attendees have been using R, their use is generally quite advanced with the vast majority using techniques to control the flow of their code (86%, 392 of 458) or writing custom R functions (85%, 389 of 458). More than half have written their own package(s) (52%, 238 of 458) and a third have publicly released a package (34%, 155 of 458).\nReflecting the distribution of length of R programming experience, the proportion of women using advanced programming techniques is slightly lower than men and when it comes to package development the proportion is lower still:\n\nThe final question we asked regarding use of R was whether the attendees use R primarily for work, recreation or both. The results were significantly different for men and women, only 22% of women (35 of 162) use R for both work and recreation compared to 45% of men (147 of 275); the few people that use R for recreation only were all men. Although factors such as age and programming experience may come into play here, it is likely that social expectations of women are also a factor. For example, although responsibility for cooking, childcare and housework is shared more evenly among working couples, in different sex couples women often shoulder a greater responsibility1. With reduced leisure time, women may be less willing to use R just for fun, or may feel less able to do so, due to expectations of their family and friends about how they should spend their free time.\n\nOverall, this paints a picture of useR! attendees as a population of mostly long-term R programmers often writing code for more than their individual use - which makes sense. As we discussed in our first post, conferences are expensive in terms of both time and money, so a conference on R is most viable for people that use R substantially in their work and hence can justify the cost to their employers. As the main conference organised by the R Foundation, useR! is particularly attractive to dedicated contributors to the R project, indeed talks and posters should present a contribution which will often be a new package or contribution to a package. This goes some way to explaining some of the inequalities in attendee demographics; we know from separate research (albeit using a rather crude metric) that CRAN maintainers, for example, are mostly not women.2\nWe have seen that the women that do attend useR! tend to be younger and less experienced. We have not explored the programming experience of other under-represented groups, for example with regard to ethnicity or sexual orientation, as the numbers in the sample are much lower, prohibiting reliable statistical conclusions and creating issues with identifiability. It is possible that, like women, members of other under-represented groups are also less likely to use R for recreation, as they will tend to have less time or money than is the norm.3 This indicates a barrier to women and other under-represented groups transitioning from useRs to developeRs: package authorship and maintenance, and dedication to an open source community, is largely uncompensated.\n\n\nOpinions about R\nThe second part of our section on R programming asked respondents for their opinions on R. On these questions there were no significant differences between the responses from men and women, so we present the results for all respondents, including non-binary individuals and those that did not declare their gender.\nWe first asked respondents how strongly they agreed or disagreed with the following statements:\n\nwriting R is fun\nwriting R is considered cool or interesting by my peers\nwriting R is a monotonous task\nwriting R is difficult\n\nThe results are presented below:\n\nWe see that respondents overwhelmingly agree that writing R is fun, so even those people that use R primarily for work enjoy doing so. The view of their peers is slightly less positive, with 12% (51 of 438) stating that writing R is not considered cool or interesting by their peers and 15% having no opinion on this (65 of 438). Even among those who agreed with the second statement, the proportion that strongly agreed is lower compared to the first statement. So although the overall picture is positive, there is a sizable group for which writing R is not encouraged by their peers, which could affect their motivation to contribute, particularly outside of work.\nThe majority (61%, 269 of 438) disagree with the statement that writing R is difficult. Those that agreed with this statement are spread across the experience levels, so some may have been expressing a general opinion about R programming rather than a personal one, necessarily. The disagreement is stronger (80%, 349 of 438) against the statement that writing R is a monotonous task, so while writing R may occasionally be difficult most useR! attendees find it challenging and interesting.\nThe generally positive view of R among useR! attendees is not so surprising, after all most will have chosen to attend the conference, or if it was required by their work they have expressed an interest in R by applying for that job or choosing to use R at work in the first place. Nonetheless, the positive view is a benefit to the community as useRs encourage people to take up R and contribute more to the R project, with many useRs being in a position to teach R, mentor junior colleagues/students or contribute to community events such as R user groups or R-ladies.\n91% (418 of 439) said that they would recommend R to friends and colleagues. The reasons some people would not recommend R include a steep learning curve, too many idiosyncrasies, poor performance and that it encourages bad programming practice. Some simply said they would recommend other software over R or they may recommend R, depending on why their friend or colleague wanted to learn a programming language.\nWhen asked to pick a single reason for recommending R, nearly 40% (160 of 425) said it was good for statistical analysis. R has long been described as the lingua franca of statistics or data science, so this makes sense. The next biggest reason was that it was good for reproducible research, indicating the increasing importance that has been put on this topic in recent years. Other important features are the package ecosystem, strength at visualization and the fact that it is free and open source." + "objectID": "about.html", + "href": "about.html", + "title": "About", + "section": "", + "text": "The task force was set up by the R Foundation in December 2015 to address the underrepresentation of women and rebranded in January 2017 to accommodate more under-represented groups such as LGBT, minority ethnic groups, and people with disabilities in the R community.\nThe members of the task force were invited to participate based on their interest in routing for specific under-represented groups and their contributions in the area of diversity and inclusion, to reflect different genders, ethnic groups, work contexts, career stages and aspects of the R project (e.g. CRAN and Bioconductor). The task force is organised as a core team plus a number of sub-teams that focus on particular tasks as outlined below:\n\nAccessibility: Working to improve access to R materials for people with low vision, blindness, hard of hearing, deaf, and other disabilities.\nCommunity: General outreach to help people from under-represented groups get into R and develop as useRs.\nConferences: Focusing on R Foundation conferences, liaising with organizers/program committee on policies and inclusion initiatives.\nOn-ramps: Creating paths for useRs to develop their skills and make contributions to the R/BioConductor package ecosystem.\nSocial Media: Posting to Twitter and/or Facebook, soliciting blog posts and publishing them, maintaining website.\nSurveys: Running and analysing community surveys, packaging up data and tools and maintaining the Data page.\nTeaching: Methodology, materials and workshops designed for under-represented groups.\n\nThe activities of the taskforce are recorded in the minutes of our bimonthly core team teleconferences and alternate monthly all team slackathons. We are open to new members joining one of our sub-teams. If interested, please contact rowforwards@gmail.com.\nThe task force is happy to engage with other individuals and organisations (such as R-Ladies) that are concerned about diversity and inclusion and actively seek outside collaboration on specific tasks." }, { - "objectID": "blog/2017/users-relationship-with-r/index.html#moving-forward", - "href": "blog/2017/users-relationship-with-r/index.html#moving-forward", - "title": "useRs Relationship with R", - "section": "Moving Forward", - "text": "Moving Forward\n\nOutreach to under-represented groups\nAs the R community seeks to be more inclusive of under-represented groups we need to be aware that individuals from these groups are less likely to have a programming background and may have less freedom to spend time on unpaid and recreational contributions. Given R’s strength as a tool for statistical analysis, introductions to R should focus on this rather than the nuts and bolts of the language, as a general rule. More experienced R programmers from under-represented groups may need additional support to transition to developeRs – even when writing packages in pure R, concepts such as version control and object-oriented programming may be new and of course interfacing with other languages such as C++ is a further stretch. We should seek to promote opportunities to under-represented groups that are paid and/or will benefit their career, e.g. Google Summer of Code projects, useR! diversity scholarships, professional development via R-ladies groups, developing a package with rOpenSci, publishing in The R Journal and so on.\n\n\nTaskforce initiatives\nFollowing our recent call to join Forwards we have set up a number of sub-teams to support women and other under-represented groups in the R community. In particular the teaching team will focus on more inclusive pedagogy, such as using examples to engage a wider demographic, and running workshops for women and girls. We have also set up a community team, to look at ways to reach out to under-represented groups and an on-ramps team to look at ways to help useRs transition to developeRs. These are all new initiatives, but we hope to get some projects off the ground in all these areas in the coming year. Anyone wishing to get involved can contact us at rowforwards at gmail dot com.\n\n\nFurther research\nSome interesting questions for further research on useRs relationship with R include:\n\nWhat programming experience do people have before using R? For example, what languages did people learn before R?\nWhy do people write packages but not publicly release them? For example, are the packages for their own use (work/recreation), for internal company use, or are the packages in development? One respondent commented that their employer prohibited releasing packages on CRAN; how widespread is this?\nWhat are the pros and cons of using R? Several respondents commented that R has many benefits but also some drawbacks and richer data could be collected on this topic." + "objectID": "about.html#background", + "href": "about.html#background", + "title": "About", + "section": "", + "text": "The task force was set up by the R Foundation in December 2015 to address the underrepresentation of women and rebranded in January 2017 to accommodate more under-represented groups such as LGBT, minority ethnic groups, and people with disabilities in the R community.\nThe members of the task force were invited to participate based on their interest in routing for specific under-represented groups and their contributions in the area of diversity and inclusion, to reflect different genders, ethnic groups, work contexts, career stages and aspects of the R project (e.g. CRAN and Bioconductor). The task force is organised as a core team plus a number of sub-teams that focus on particular tasks as outlined below:\n\nAccessibility: Working to improve access to R materials for people with low vision, blindness, hard of hearing, deaf, and other disabilities.\nCommunity: General outreach to help people from under-represented groups get into R and develop as useRs.\nConferences: Focusing on R Foundation conferences, liaising with organizers/program committee on policies and inclusion initiatives.\nOn-ramps: Creating paths for useRs to develop their skills and make contributions to the R/BioConductor package ecosystem.\nSocial Media: Posting to Twitter and/or Facebook, soliciting blog posts and publishing them, maintaining website.\nSurveys: Running and analysing community surveys, packaging up data and tools and maintaining the Data page.\nTeaching: Methodology, materials and workshops designed for under-represented groups.\n\nThe activities of the taskforce are recorded in the minutes of our bimonthly core team teleconferences and alternate monthly all team slackathons. We are open to new members joining one of our sub-teams. If interested, please contact rowforwards@gmail.com.\nThe task force is happy to engage with other individuals and organisations (such as R-Ladies) that are concerned about diversity and inclusion and actively seek outside collaboration on specific tasks." }, { - "objectID": "blog/2017/users-relationship-with-r/index.html#notes", - "href": "blog/2017/users-relationship-with-r/index.html#notes", - "title": "useRs Relationship with R", - "section": "Notes", - "text": "Notes\nWe do not plan to release the raw survey data as many individuals can be uniquely identified from one or two demographic questions. We may release the data in an aggregated form once we have completed our full analysis (this post covers the second of three sections).\nThe analysis presented here used the following packages:\n\nFor data manipulation: dplyr, forcats, purrr, tidyr\nFor visualization and reporting: knitr, ggplot2, likert\n\nThe code is available in the Rmarkdown file.\nThe banner image was based on the plotHeart function written by Sandy Kawano for Valentine’s Day, based on this answer to a Stackoverflow post." + "objectID": "about.html#core-members", + "href": "about.html#core-members", + "title": "About", + "section": "Core Members", + "text": "Core Members\nHeather Turner - Chair and ‘On-ramps’ team leader. Heather is a Research Software Engineering Fellow in the Statistics department at the University of Warwick and is on the board of the R Foundation. (LinkedIn/Mastodon/ GitHub)\ngwynn gebeyehu - Administrator and ‘Accessibility’ team leader. gwynn completed a post-doc at Harvard Business School and co-founded of the Harvard Data Science Initiative R User Group. (Mastodon)/GitHub)\nJonathan Godfrey - ‘Accessibility’ team leader. Jonathan was the first totally blind person in the world to gain employment as a Lecturer in Statistics (Massey University, NZ). (Twitter/GitHub)\nKevin O’Brien - ‘Community’ team leader. Kevin is a data scientist working for a forestry company, modelling forestry resources, as well as one of the main organizers of Dublin R. (LinkedIn/Twitter/GitHub)\nElla Kaye - ‘Community’ team leader. Ella is a statistician and R enthusiast. She’s a founding member of RainbowR and a previous co-organiser of the Oxford R User Group. (LinkedIn/Mastodon/GitHub)\nYanina Bellini Saibene - ‘Conferences’ team leader. Yanina is a professor at national universities in Argentina and Uruguay and a researcher who applies data science to the agricultural sector. She is co-founder of MetaDocencia, part of the R-Ladies Global Team, co-founder and chair of LatinR, chair of useR! 2021, chair of the 49 & 50 JAIIO, and chair of the AgroInformatics Congress. (LinkedIn/Twitter/GitHub)\nNoa Tamir - ‘Conferences’ team leader (on leave). Noa is a Data Science Manager, an organizer of the R-Ladies Berlin and Women in Machine Learning and Data Science Berlin Meetups, and has recently organized the satRday Berlin 2019 conference. (LinkedIn/Twitter/GitHub)\nSaranjeet Kaur Bhogal - ‘On-ramps’ team leader. Saranjeet volunteers for the R-Ladies Global Team. She is a Statistician by training and likes to work for open source and open science. (LinkedIn/Twitter/GitHub)\nTatjana Kecojevic - ‘Surveys’ team leader. Tanja is a statistician, instructor and consultant. She is the founder of Sister Analyst, an NGO devoted to empowering women and other under-represented groups, in the field of data literacy and science. Tanja is also the founder and co-organiser of the R-Ladies Manchester and Belgrade chapters. Her enthusiasm for data science is matched by her commitment to inclusivity. Data skills should be accessible to anyone with a desire to discover. (LinkedIn/Twitter/GitHub)\nAndrea Sánchez-Tapia - ‘Surveys’ team leader. Andrea is a computational biologist, working with biodiversity informatics and open and reproducible workflows in ecology. She teaches R and other computational skills in academic and non-academic environments, and co-organizes R-Ladies Rio de Janeiro. (Twitter/GitHub)\nAnna Vasylytsya - ‘Surveys’ team leader. (LinkedIn/GitHub)\nMine Çetinkaya-Rundel - ‘Teaching’ team leader. Mine is a Professor at Duke University and Data Scientist & Professional Educator at RStudio. (LinkedIn/Twitter/GitHub)\nEmma Rand - ‘Teaching’ team leader. Emma is a Senior Lecturer (Associate Professor) at the University of York, UK and teaches reproducible data analysis to bioscientists in her institution and with the Royal Society of Biology and the Biochemical Society. (LinkedIn/Twitter/GitHub)" }, { - "objectID": "blog/2017/users-relationship-with-r/index.html#footnotes", - "href": "blog/2017/users-relationship-with-r/index.html#footnotes", - "title": "useRs Relationship with R", - "section": "Footnotes", - "text": "Footnotes\n\n\nhttps://www.familiesandwork.org/downloads/modern-families.pdf↩︎\nhttps://forwards.github.io/data/#maintainer_gender_2016↩︎\nFor example, average earnings in the US are lower for many ethnic minorities in general and in science and engineering occupations in particular, including computer and information science specifically (https://www.nsf.gov/statistics/2017/nsf17310/static/data/tab9-17.pdf). The American Association of University Women report that gay and bisexual men tend to be paid less than similarly qualified heterosexual men; while trans women (who have transitioned from male to female) experience a drop in pay. They also report that transgender people frequently face harassment and discrimination; this may affect their motivation for voluntary contribution (http://www.aauw.org/resource/the-simple-truth-about-the-gender-pay-gap/).↩︎" + "objectID": "about.html#sub-team-members", + "href": "about.html#sub-team-members", + "title": "About", + "section": "Sub Team Members", + "text": "Sub Team Members\nZane Dax - ‘Accessibility’ team member. (Twitter/GitHub)\nLiz Hare - ‘Accessibility’ team member. (LinkedIn/Mastodon/GitHub)\nFlorencia Mangini - ‘Accessibility’ team member. (Twitter/GitHub)\nBecca Wilson - ‘Accessibility’ team member. (LinkedIn/Twitter)\nTania Allard - ‘Community’ team member. (LinkedIn/GitHub)\nDamiano Cerasuolo - ‘Community’ team member. (LinkedIn/Twitter/GitHub)\nJoslynn Lee - ‘Community’ team member. (LinkedIn/Twitter/GitHub)\nSamantha Toet - ‘Community’ team member. (LinkedIn/Twitter/GitHub)\nJulie Josse - ‘Conferences’ team member. (LinkedIn/Twitter/GitHub)\nImke Mayer - ‘Conferences’ team member. (LinkedIn/Twitter/GitHub)\nMiljenka Vuko - ‘Conferences’ team member. (LinkedIn/Twitter/GitHub)\nJyoti Bhogal - ‘On-ramps’ team member. (LinkedIn/Twitter/GitHub)\nMichael Chirico - ‘On-ramps’ team member. (Twitter/GitHub)\nMaya Gans - ‘On-ramps’ team member. (Twitter/GitHub)\nMichael Lawrence - ‘On-ramps’ team member. (LinkedIn/Twitter/GitHub)\nPavitra Chakravarty - ‘Surveys’ team member. (Twitter/GitHub)\nPaola Corrales - ‘Surveys’ team member. (Twitter/GitHub)\nNujcharee Haswell - ‘Surveys’ team member. (LinkedIn/Twitter/GitHub)\nClaudia Huaylla - ‘Surveys’ team member. (Twitter/GitHub)\nDi Cook - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)\nEmily Dodwell - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)\nIsabella Gollini - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)\nRitwik Mitra - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)\nMaria Prokofieva - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)\nJoyce Robbins - ‘Teaching’ team member. (LinkedIn/Twitter/GitHub)" }, { - "objectID": "blog/2018/r-in-latin-america/index.html", - "href": "blog/2018/r-in-latin-america/index.html", - "title": "R in Latin America", - "section": "", - "text": "Following on from our post on R in Africa this next post in the series looks at the R community across Latin America." + "objectID": "about.html#previous-members", + "href": "about.html#previous-members", + "title": "About", + "section": "Previous Members", + "text": "Previous Members\nRichard Ngamita Lorna Maria Aine\nStella Bollman\nJenny Bryan\nNic Crane\nRudolf Debelak\nJohn Fox\nJasmine Dumas\nAndrea Foulkes\nGina Griffin\nMadlene Hamilton\nZhian N. Kamvar\nLiz Kellogg\nOs Keyes\nAngela Li\nGina Merchant\nDavid Meza\nIleena Mitra\nJesse Mostipak\nShakirah Nakalungi\nWenfeng Qin\nAugustina Ragwitz\nMaëlle Salmon\nDorris Scott\nTracy Shen\nDavid Smith\nCarolin Strobl\nCharlotte Wickham\nHadley Wickham\nYizhe Xu" }, { - "objectID": "blog/2018/r-in-latin-america/index.html#conferences", - "href": "blog/2018/r-in-latin-america/index.html#conferences", - "title": "R in Latin America", - "section": "Conferences", - "text": "Conferences\nAs the use of R has grown in Latin America, there has been an increasing demand for local R conferences. The community has responded and a number of conferences are planned for the coming months.\n\nInternational Seminar on Statistics with R\nOne of the first to spot the demand was Luciane Alcoforado, a professor at the Fluminense Federal University (UFF) in Rio de Janeiro, Brazil. Realizing there was no large R event in Brazil, she set about coordinating the first International Seminar on Statistics with R (SER: Seminário Internacional de Estatística com R), which was held in Niterói in May 2016.\n Luciane Alcoforado, Coordinator of the first SER\nMore than 250 people attended this pioneering event, with attendance balanced across academia and industry. Encouraged by this success, the I SER organizers ran the event again in 2017, with an expanded program and similar numbers attending.\n Sean Kross presents remotely at the first SER\nA third edition, III SER, is now planned for May 22-24, 2018, to be hosted again by UFF in Niterói, Brazil. On the first day, 8 mini courses will be run, aimed at both practitioners and students. This year most of the international guests come from the USA and England. They include Jesse Mostipak, Becky Pattinson, Garreth Maccray, and Gabriela de Queiroz. These guests will present alongside invited speakers from the local region. There will also be thirty selected contributed talks and a poster session with awards for the best three of each. It’s a huge opportunity to get your research known. The last conference day will close with a tribute session to Prof. Djalma Pessoa who was a pioneer R user in Brazil.\nRegistration to III SER and the mini-courses is open now and the call for papers is open until March 23 2018.\n\n\nR Day\nA second event in Brazil, R Day, will take place at the Federal University of Paraná (UFPR), Curitiba, on May 22, 2018. The Statistics Department at UFPR was one of the first in Brazil to adopt R as the standard programming language for statistics teaching, in 2002. It was also the first institution to host a CRAN mirror in the country, and started the R-br mailing list in 2011, which now has more than 1000 subscribers.\nThe R Day is organized as a satellite event of the 63rd RBRAS meeting (Brazilian Region of the International Biometric Society), and is endorsed by the R Foundation to further develop the academic R community in Brazil. There will be three keynotes, 9 oral presentations, and 8 tutorials, aimed at both users and developers. The main goal is to be community-driven, so anyone can submit proposals for oral presentations and/or tutorials (only the three keynote speakers will be invited by the organizers).\nThe aim of R Day is to gather the vast R community in Brazil, by offering the possibility for users and developers to show their work and exchange experience on all sorts of R subjects. Proposals for oral presentations and tutorials are open until April 04. The registration is free and can be made until April 22.\nFor more information and updates, registration and proposal forms, checkout the R Day website, and follow us on Facebook and Twitter.\n R Day logo (left), Curitiba Botanical Garden (top right), and UFPR historical building (bottom right)\n\n\nsatRday Bogota\nThe first Latin American chapter of the one day conference series satRdays will take place in Bogota, Colombia in August 2018. The focus of the conference will be about tidy concepts applied to data visualization. It is organized by Datasketch, a Data Journalism Portal for Latin America.\nThe main goal of the conference is to create a common space for interaction among newbies and experts in R. Special interest will be given to works created by or for underrepresented communities and to showcase different solutions developed using R for the different elections that are happening in 2018 in different Latin American countries.\nThere are tentative plans for a workshop session the day before with hands-on tutorials about:\n\nData visualization and common mistakes.\nData structuring and preparation: PDFs, Databases and API’s.\n\nA website containing more details will be available soon.\n\n\nLatinR\nOn October 25, 2017, an announcement was made by Heather Turner on the RUG Organizers Slack: the R Foundation Conference Committee would like to see academic-focused R events in regions not currently covered by useR! In less than a week, a group of Latam R-Ladies were organizing their first conference-call to start thinking about how this challenge could be achieved. This quick response was not the result of mere chance, but the consequence of a year in which the R community — both RUG and R-Ladies groups — grew stronger in South America. By mid November everything was set-up: a name, a place, a date, and a motivated international organizing committee.\nLatinR 2018 will be held in Buenos Aires on September 4-5 within the 47th Argentinian Meeting of Informatics and Operational Research (JAIIO), which is organized by The Argentinian Informatics Society (SADIO). With a diverse and renowned Scientific Committee, this two-day event aims to bring together researchers, students, and R-enthusiasts from different backgrounds in order to strengthen the R community and make the impact that R is having in the region more visible, in both academic and non academic contexts.\nFor more information about oral presentations & poster submission, keynotes, and workshops, you can check out the LatinR website or follow us on Twitter and Facebook: @LatinR2018.\n\n\nConectaR 2019\nIn 2019, it is Costa Rica’s turn: ConectaR 2019 will take place in San José. The event has the endorsement of R Foundation and will be hosted at the University of Costa Rica (UCR). ConectaR has an organizing committee comprising members of academia (School of Statistics, Pure and Applied Mathematics Research Center (CIMPA)), public research centers (The Development Observatory, Bioversity International (CGIAR)) and industry (ixpantia). ConectaR will have two keynote speakers (yet to be confirmed) and will be receiving proposals for oral presentations and posters starting April 2018. In addition to that, there will be tutorials, invited talks, and a job fair. An attendance of over 150 people is expected, with the goal of building a community of R users in the Central American Region." + "objectID": "blog.html", + "href": "blog.html", + "title": "Blog", + "section": "", + "text": "Our blog is aggregated by R Weekly and R Bloggers.\n\n\n\n\n\n\n \n \n \n Order By\n Default\n \n Title\n \n \n Date - Oldest\n \n \n Date - Newest\n \n \n Author\n \n \n \n \n \n \n \n\n\n\n\n \n\n\n\n\nBlackLivesMatter: A joint statement by Forwards and R-Ladies\n\n\n\n\n\n\n\ncommunity\n\n\nnews\n\n\n\n\n#BlackLivesMatter: A joint statement by Forwards and R-Ladies\n\n\n\n\n\n\nJun 6, 2020\n\n\n\n\n\n\n \n\n\n\n\nSouthern Africa Project 2020\n\n\n\n\n\n\n\ncommunity\n\n\neducation\n\n\nsoftware\n\n\n\n\nReview of the R training and community events organized as part of the Forwards Southern Africa Project 2020, in South Africa, Eswatini and Botswana.\n\n\n\n\n\n\nMay 25, 2020\n\n\nHeather Turner\n\n\n\n\n\n\n \n\n\n\n\nRecap of R-Ladies Charlottesville Forwards Workshop\n\n\n\n\n\n\n\neducation\n\n\nsoftware\n\n\ncommunity\n\n\n\n\nLessons from R-Ladies Charlottesville Forwards Workshop\n\n\n\n\n\n\nNov 22, 2019\n\n\nAngela Li, Samantha Toet\n\n\n\n\n\n\n \n\n\n\n\nThe state of R in Africa\n\n\n\n\n\n\n\nnews\n\n\ncommunity\n\n\n\n\n2019 Round-up of initiatives in the R community across Africa.\n\n\n\n\n\n\nNov 15, 2019\n\n\nLorna Maria\n\n\n\n\n\n\n \n\n\n\n\nWorkshops for Women and Girls\n\n\n\n\n\n\n\neducation\n\n\nsoftware\n\n\ncommunity\n\n\n\n\nRound up of Forwards workshops supported by a grant from the R Consortium, to develop R package development skills among women and R coding skills among high school girls.\n\n\n\n\n\n\nSep 22, 2019\n\n\nForwards Teaching Team\n\n\n\n\n\n\n \n\n\n\n\nHavanaR Workshop 2018\n\n\n\n\n\n\n\nnews\n\n\ncommunity\n\n\neducation\n\n\n\n\nAnnouncement of joint >eR-Biostat and Forwards workshop in Havana, on visualisation methods and exploratory analysis of high dimensional and multivariate datasets in R.\n\n\n\n\n\n\nJul 7, 2018\n\n\nZiv Shkedy, Julie Josse\n\n\n\n\n\n\n \n\n\n\n\nR in Latin America\n\n\n\n\n\n\n\nnews\n\n\ncommunity\n\n\n\n\nRound-up of initiatives in the R community across Latin America.\n\n\n\n\n\n\nFeb 5, 2018\n\n\nAriel Levy, Fernando Mayer, Juan Pablo Marín Díaz, Riva Quiroga, Marcela Alfaro, Alejandro Reyes, Heather Turner\n\n\n\n\n\n\n \n\n\n\n\nR in Africa\n\n\n\n\n\n\n\nnews\n\n\ncommunity\n\n\n\n\nRound-up of initiatives in the R community across Africa.\n\n\n\n\n\n\nDec 1, 2017\n\n\nAndrew Collier, Anelda van der Walt, Ziv Shkedy, Theoni Photopoulou, Margareth Gfrerer, Heather Turner\n\n\n\n\n\n\n \n\n\n\n\nGirls Coding Workshop, Melbourne\n\n\n\n\n\n\n\neducation\n\n\nsoftware\n\n\ncommunity\n\n\ntraining\n\n\nteaching\n\n\n\n\nGirls Coding Workshop, Melbourne\n\n\n\n\n\n\nNov 20, 2017\n\n\nDi Cook\n\n\n\n\n\n\n \n\n\n\n\nuseRs Participation in the R Community\n\n\n\n\n\n\n\nanalysis\n\n\nuseR!\n\n\nsurvey\n\n\ncommunity\n\n\n\n\nCommunity Involvement of useRs\n\n\n\n\n\n\nJun 19, 2017\n\n\nStella Bollmann, Dianne Cook, Rudolf Debelak, Jasmine Dumas, John Fox, Julie Josse, Oliver Keyes, Carolin Strobl, Heather Turner”\n\n\n\n\n\n\n \n\n\n\n\nuseRs Relationship with R\n\n\n\n\n\n\n\nanalysis\n\n\nuseR!\n\n\nsurvey\n\n\nprogramming\n\n\n\n\nReport on programming section of useR! 2016 survey\n\n\n\n\n\n\nMar 11, 2017\n\n\nStella Bollmann, Dianne Cook, Rudolf Debelak, Jasmine Dumas, John Fox, Julie Josse, Oliver Keyes, Carolin Strobl, Heather Turner\n\n\n\n\n\n\n \n\n\n\n\nEmily Robinson, from Social Scientist to Data Scientist\n\n\n\n\n\n\n\ninterviews\n\n\ndata science\n\n\ncareers\n\n\n\n\n\n\n\n\n\n\n\nFeb 7, 2017\n\n\nMaëlle Salmon\n\n\n\n\n\n\n \n\n\n\n\nCall to Join Forwards\n\n\n\n\n\n\n\nnews\n\n\naction\n\n\n\n\nInviting New Members to join Forwards\n\n\n\n\n\n\nJan 13, 2017\n\n\n\n\n\n\n \n\n\n\n\nMapping useRs\n\n\n\n\n\nReport on demographics section of useR! 2016 survey\n\n\n\n\n\n\nJan 13, 2017\n\n\nStella Bollmann, Dianne Cook, Rudolf Debelak, Jasmine Dumas, John Fox, Julie Josse, Oliver Keyes, Carolin Strobl, Heather Turner\n\n\n\n\n\n\nNo matching items" }, { - "objectID": "blog/2018/r-in-latin-america/index.html#other-initiatives", - "href": "blog/2018/r-in-latin-america/index.html#other-initiatives", - "title": "R in Latin America", - "section": "Other Initiatives", - "text": "Other Initiatives\n\nR/Bioconductor Latin American Developers’ Workshop\nIn recent years, biology has seen a rise in the use of technologies that enable high-throughput, quantitative, data-rich profiling of cellular states. As a result, the field faces computational challenges to analyse such data. The R/Bioconductor project is an open source, open development software platform that provides tools to translate complex data sets into biological knowledge. An R/Bioconductor workshop will be held in Cuernavaca, Mexico on July 30 - Aug 3, 2018.\nThe workshop is aimed at students and researchers interested in the analysis of biological data. We encourage applications from diverse disciplines, including but not limited to biologists, bioinformaticians, data scientists, software engineers and programmers. The main goals of the workshop are:\n\nTeaching participants the principles of reproducible data science through the development of R/Bioconductor packages.\nTurning bioinformatic software users into bioinformatic software developers.\nFostering the exchange of expertise and establishing multidisciplinary collaborations.\nCreating a community of Latin American scientists committed to the development of software and computational pipelines for biological data analysis.\nHelping to train bioinformatics instructors that can continue to grow in their local communities.\n\nThis workshop is part of a long-term project to create a community of developers from Latin America. We hope to hold regular meetings in the future (similar to BioC, EuroBioc and BioCAsia) where attendees present their own software contributions.\nA website containing more details will be available soon.\n\n\nLocal groups\nBeyond conferences and workshops, local groups provide a venue for R users to meet more regularly. Jumping Rivers provide a user group directory, which also covers R-Ladies groups, however as R-Ladies are expanding rapidly it is worth checking the R-Ladies Starter Kit for the latest status.\nRecently members of the RUG and R-Ladies groups in Bogota, Columbia collaborated on a striking intervention about feminicides in Colombia using plots created in R. Read more on their initiative in this report (warning: readers may find the content distressing). This is an example of how local groups can work together on wider issues as well as providing networking and development opportunities for their members.\n\n\nMaking Connections\nPart of building the community in Latin America is making connections between disconnected groups. If you think we have missed something, or you would like to be involved in plans for future events in the region, let us know in the comments or contact us on email (rowforwards at gmail dot com) or Twitter.\nBanner image shows the poster session at I SER." + "objectID": "blog/2017/emily-robinson-interview/index.html", + "href": "blog/2017/emily-robinson-interview/index.html", + "title": "Emily Robinson, from Social Scientist to Data Scientist", + "section": "", + "text": "Maëlle Salmon, a Forwards collaborator, got the chance to interview Emily Robinson, who recently became a data analyst at Etsy. A very inspiring R-Lady!\n\nHi, Emily! Thanks for letting us interview you! You studied Decision Sciences at Rice University and then graduated from INSEAD with a Master’s degree in Management (specialization in Organizational Behavior). What are those fields? How do they help you today?\nDecision Sciences was an interdisciplinary major I actually created at Rice in my sophomore year based on Carnegie Mellon’s major. Before then I’d been planning to major in economics or psychology, but I found that neither really satisfied what I was looking for: to understand how people make decisions. So I decided to take the rarely used option at Rice to design my own curriculum with the input of many faculty members, and I created a course list that was a mix of economics, psychology, statistics, and philosophy.\nOrganizational Behavior is a pretty broad field, but essentially is the application of sociology and psychology applied to organizations/work. So people study everything from the effect of power on behavior to the benefits and pitfalls of multicultural teams to how social activists affect corporate political activity. I focused more on the micro (psychology) side and studied women in STEM fields.\nAll of the statistics courses I took have definitely helped. Also, the data science project process is actually quite similar to social sciences research: you come up with a question or a hypothesis, gather and clean the data, run an analysis, and communicate your findings.\nFinally, I think there’s often a place for knowledge about human and organizational behavior to come into the data science research process. I talked a lot in my interviews about how social sciences knowledge could be used in designing experiments; for example, the fact that giving people more choices actually makes them less likely to buy something, or that people from different countries use satisfaction scales differently (e.g. an American and a German may be equally satisfied with a product, but because of cultural reasons the German gives a lower score on a scale out of 10).\nYou then decided to become a data scientist instead. What motivated this decision? (Also, note we now assume you make decisions in a smarter way than most of us, given the name of your college major!)\nShort answer: I felt data science was where the most interesting questions, tools, and data were. I also believe that working as a data scientist/analyst offers a bigger possibility for broad impact than academia. While there’s definitely a lot of interesting and important research being done in academia, it’s a very long, slow process, with a lot of luck, and often times doesn’t reach anyone outside of the ivory tower. If anyone wants the longer story, please feel free to reach out to me on twitter/email.\nWhen did you first come in contact with R? Was it love at first sight? From which point did you feel enough at ease to be not only a R user, but also a R programmer?\nI was very lucky to do my undergraduate degree at Rice University, where at the time Hadley Wickham was a Statistics Professor. I only took one course with him, an Introduction to Statistics course, which didn’t involve R, but he had also designed later courses that were taught by his graduate students. At the time I didn’t realize how prominent in the R community he was, despite my brother Dave Robinson (then a PhD student at Princeton, now a data scientist at StackOverflow) shouting at me how cool it was that I was being taught by Hadley.\nBecause the courses were so well-designed and taught, I definitely fell in love with R at first sight. Despite its reputation as having a steep learning curve, I found it fairly straight forward to pick up (or maybe I’m just romanticizing it in my memories). That being said, I didn’t use it much outside of my statistics courses that required it, except to make a few plots for one of my research projects. It was in graduate school that I started to use R of my own volition. As I wrote about in one of my blog posts, I got so frustrated with using STATA, the language of choice for my graduate program, for certain class assignments that I switched to using R.\nI think this transition from being an R user to R programmer was also helped by some new tidyverse packages that came out in the last few years, especially dplyr. While the packages I initially learned, like reshape2 and plyr, were great, R has clearly advanced in the four years since I did most of my R courses.\nWhat is this program you’ve done for transitioning into your new career and how did you hear about it? How much can one learn in 12 weeks?\nMetis is a Data Science Bootcamp that helps people transition into careers as a Data Scientist/Analyst. I heard about it from my brother, who had spoken at Metis and gone to their career day, where students present their final projects to recruiters and data scientists. He had been really impressed by the quality of the students and their work, and so I looked into the program more. I found that it fit perfectly my background, as what I was missing was Python skills and Machine Learning knowledge. Metis is not meant to take you from 0 to 60; everyone who enters the program has some knowledge of statistics and programming, although their backgrounds still vary widely. In my cohort, we had people a few years out of college, one person with twenty years of marketing experience, and a few with PhDs in quantitative fields.\n Emily’s Metis cohort plus the two instructors (two people on the right)\nIn terms of what you can learn in 12 weeks, Metis is not meant to make you an expert in everything they cover. Rather, by giving you exposure to many topics and having you do projects around them, you get a good enough grounding so that you can continue learning on your own. It also gives you a portfolio of projects that you can host on your GitHub and talk about during interviews. The other big benefit is the career support from the Metis career team and from the extensive alumni network. You receive help in making a resume and prepping for interviews, but also in connecting you to people at the companies you’re interested in. For me it was 100% worth it. It was also a lot of fun and I met some great people!\nYou had to use Python at Metis: Which language do you use the most now? Could you use only Python?\nSince I just started my position, I’m not sure which language I’ll be using more. Etsy is pretty agnostic for which language its analysts use, and a lot of the work is done in SQL since we are working with such big datasets. If I had too, I could definitely use only Python, since I did use it so intensely for those few months. But I’m still definitely biased towards R and will probably be using that more.\nYou have just started a job at Etsy as a data scientist (congrats!). Could you tell us a little bit more about your job there? What kind of problems do you solve? How is the work organized between members of your team?\nThank you! My official title is actually Data Analyst and I’m on the analytics team; Data Scientists at Etsy are on the engineering (production) side and generally have PhDs in Computer Science/Machine Learning or similar backgrounds. While the analytics team sits together, we are embedded with other teams and serve as a sort of consultant, helping those teams improve how they use and analyze their data, run experiments, etc. For example, we have analysts working with marketing, accounting, seller services, etc.\nI’ll be working on search, which I’m very excited about since search is such a big part of the Etsy experience. Etsy actually just acquired BlackBird Technologies and their team to bring AI into their search, which should offer a lot of new opportunities. I’ll be working closely with another senior analyst and the broader search sciences team.\nThat all being said, Etsy does a great job with orientation and the first few weeks are dedicated to meeting people, reading analytics on-boarding materials, and getting my tech stack set up. So I haven’t heard anything yet about what specific projects I’ll be working on and won’t for a little while.\nWhat would you wish to have known sooner on your way to become a data scientist?\nDon’t be intimidated! It’s easy to feel like unless you have a PhD in Machine Learning and are an expert in Big Data that there are no roles for you. This isn’t helped by the fact that some companies’ job postings read like a wish list for a Data Scientist unicorn. But if you’ve been working on building your skills, you can find a position for you. You also DO NOT need to necessarily meet all of the job requirements; don’t be afraid to apply to a job where you’re just missing one of multiple criteria, or you have a year or two fewer years of experience than they mention.\nAnd as with almost every job, networking is critical. At some companies, there are thousands of people applying for each position, and having someone refer you can really help you get your foot in the door. Even more than that, talking to someone about the culture and day-to-day work in a company will really help you in your interview, because you’ll know more about what they’re looking for and if you’re a good fit.\nFinally, don’t be hung up on titles and only focus on positions where the title is “Data Scientist”. The work you’re doing is what’s important, and some data analysts are doing work that at other companies would be classified as a data scientist job. My title is a Data Analyst (as was Hilary Parker’s when she started out at Etsy), and while I’m not going to be doing deep learning projects anytime soon, I don’t think there’s going to be any shortage of interesting and challenging work.\nYou mention the importance of giving back to the open-source community on your blog, Hooked on Data. What are your plans with the blog and your programming in general? (Please keep writing on your blog!)\nOne big thing I want to do is host some in-person R tutorials for the R-Ladies NYC group. They had their kick-off meeting a few weeks ago, and many people expressed interest in an introduction to R tutorial and a more advanced one. While there are definitely some good resources online, my favorites are DataCamp for interactive tutorials and Hadley and Garrett’s new R for Data Science book, I do think it can sometimes be easier to learn in person. I tried to get more people in my graduate program (including professors!) to use R, so I’d love to help a group that already recognizes the value of R and is eager to learn.\nOther than that, I definitely want to keep blogging. I think a lot of my work at Etsy is going to be confidential, so I won’t be able to share that, but hopefully I’ll be able to talk about some cool side projects I’m doing or general principles I learned from my work. I’ve promised posts about making my first R package and my final Metis project, so I’d better get going on those!\nP.S. DataCamp has a few free courses, but if anyone wants to try unlimited access you can do so for free for two days with this link. There’s some really great courses, including one by Hadley and his sister Charlotte, and another by my brother!\nLast but not least, we were thrilled to learn you are a RCatLady although you don’t have a cat! Also you have a dog! Is she a good R-Dog?\n Emily’s R-Dog Abby\nShe is the best R-Dog. I’m very excited that Etsy is a dog-friendly office, and I plan to take her into the office sometime soon. I’m sure she’ll be very well-behaved; she spends most days sleeping on her bed or sitting under my mom’s desk at home right by her feet.\nOkay now we are very jealous! Thanks again Emily for talking with us, all the best for the future!\nContact Emily via her email address (robinson.es at gmail dot com), go read her blog, follow her on Twitter, Github, or LinkedIn.\nDisclaimer: The views expressed in this interview represent Emily’s own views and opinions, not necessarily those of Etsy.\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" }, { - "objectID": "blog/2019/the-state-of-r-in-africa/index.html#growth-of-the-r-ecosystem-in-africa", - "href": "blog/2019/the-state-of-r-in-africa/index.html#growth-of-the-r-ecosystem-in-africa", - "title": "The state of R in Africa", - "section": "Growth of the R ecosystem in Africa", - "text": "Growth of the R ecosystem in Africa\nOver the past 2 years, we have seen R transform from just an academic and health care research language to one of the major languages in the budding data science community in Africa. For a long time, data scientists and related disciplines have relied on R and many other packages to analyse data, however, the broader developer community didn’t fully understand its power in the tech industry. An effective model to enter the Africa developer ecosystem relies on a small group of enthusiasts creating a safe learning environment, documenting and sharing their learning experiences and slowly attracting interested learners. Africa R users group are using this model to introduce R as a language for data science by organising communities across different cities in Africa." + "objectID": "blog/2017/mapping-users/index.html", + "href": "blog/2017/mapping-users/index.html", + "title": "Mapping useRs", + "section": "", + "text": "Every year, hundreds of R programmers descend on a host city and spend three or four days sharing work, collaborating on projects and making new contacts - the useR! conference, this year held in Stanford, CA. useR! offers a wonderful opportunity to map a subset of the language’s most active users and the Women in R Task Force took this opportunity to survey attendees and find out their backgrounds, experiences and interests, in the hope that it will help us to get a better understanding of how to make the R community a more inclusive environment.\nOur survey received 455 responses, out of 899 attendees, and appears to represent the attendees pretty accurately.1 In this blog post, we’ll step through the attendees’ demographic background, how that represents the wider scientific and computing communities (and wider world), and propose recommendations for ways to bring these demographics towards parity." }, { - "objectID": "blog/2019/the-state-of-r-in-africa/index.html#evolution-of-chapters-and-representation", - "href": "blog/2019/the-state-of-r-in-africa/index.html#evolution-of-chapters-and-representation", - "title": "The state of R in Africa", - "section": "Evolution of chapters and representation", - "text": "Evolution of chapters and representation\nThe growth of technical talent in Africa positively correlates with the growth of communities around certain technologies/tools/languages. These communities are creating a long table to share opportunities on the continent. When we shift the spotlight to R in the Africa tech community we see an evolution in useR groups of not only academic researchers using R in their PhD or master’s degrees but also people using R at their workplaces or for their freelance projects. There is a unique representation in the Africa R community that shows how the useRs have created a safe space for equal active participation. Global communities like R Ladies and Women in Machine Learning and Data Science have given so many women in the community a platform to start R user groups in their localities. The support from these groups has contributed to the early success of R user groups as the safest places to start your data science career. \nSome of the chapters include Kampala,Lagos,Dar es salaam, Abidjan, Johannesburg,[DRC] (https://mobile.twitter.com/DrcUsers),Cotonou among others." + "objectID": "blog/2017/mapping-users/index.html#summary", + "href": "blog/2017/mapping-users/index.html#summary", + "title": "Mapping useRs", + "section": "Summary", + "text": "Summary\nSurvey responses showed that attendees were largely male and white, with Latinx, Native American and people of African descent particularly under-represented. Attendees were almost all employed, and what’s more, employed in a permanent, full-time job. Attendence skewed heavily towards people in their late 20s and early to mid 30s, with men tending to be older than women, and attendees largely coming from the United States and almost exclusively from North American and Western European countries.\nOur recommendations are that, going forward, useR! conferences set aside tickets and funding for under-represented groups, and put resources into facilities such as feeding rooms and childcare that would benefit caregivers with small children, many of whom are women. Additionally, the Task Force itself will be refocusing its efforts and mission to emphasise the intersectional nature of marginalisation that women face, in line with the dispiriting results around race, employment and educational attainment. We will also be running further surveys to build up a better idea of the “ground truth” of the R community, and to track improvements and suggestions on an ongoing basis." }, { - "objectID": "blog/2019/the-state-of-r-in-africa/index.html#events", - "href": "blog/2019/the-state-of-r-in-africa/index.html#events", - "title": "The state of R in Africa", - "section": "Events", - "text": "Events\nMonthly Meetups: These are the most popular events in the community. Groups of 10-50 useRs meet every month to learn and help each other with R related issues. They are usually supported by the local useR group in the area and are at the forefront of the growing popularity of data science in the local communities.\nSatRday: The R community in Johanessburg and Kampala have both hosted satRday events in April 2019 and May 2019 respectively. These events featured lightning talks and hands-on workshops for R users and were free. These have been the biggest R focused events on the continent for the year and the hope is they will spread to other regional hosts in the coming year." + "objectID": "blog/2017/mapping-users/index.html#survey-results", + "href": "blog/2017/mapping-users/index.html#survey-results", + "title": "Mapping useRs", + "section": "Survey results", + "text": "Survey results\n\nGender and race\nThe gender breakdown of responses (n=453) showed that approximately 33% of attendees identified as women, with the majority of the remainder identifying as men and a small number identifying outside the gender binary.\nWhile the inclusion of women is not as bad as at other conferences, it’s also definitely lower than it could be given that there are many scientific fields - such as biology, which R is particularly commonly used in - where women outnumber men in terms of degree attainment.2 At the same time, some of this may be offset by the location and chosen topics for presentations, which were more focused on visualisation or computing than biostatistics.\nRace is more complicated, because there’s more variation in the answers - as intended! Both race and gender questions were offered as a free text field to avoid restricting respondents to false dichotomies. One side-effect, though, is that it’s hard to aggregate the data. What we can say, though, is:\n\n74% of respondents identified as White or Caucasian;\n16% fell within the US Federal guidelines for ‘Asian’, or identified directly as Asian;\n3% identified as Hispanic or Latinx;\n1% identified as people of African descent;\n0.5% identified as Native American or Pacific Islander;\n0.25% identified as Middle Eastern and\n3% identified as mixed-race.\n\nIn comparison, a survey of STEM workers in the United States found 6% were Black and 7% Hispanic3 4 - and the overall demographics of the United States point even more clearly to an under-representation of non-Asian minority groups.5 The response rate was somewhat lower on this question (n = 409), perhaps due to concerns about identifiability. Nonetheless, there’s clearly work to be done.\n\n\nLGBT\n5% of respondents identified as Lesbian, Gay, Bisexual or Transgender. How this maps to overall industry, academic and population trends is hard to identify, because the long history of persecution of LGBT individuals and the often confusing and ill-defined nature of identity means that the proportion of LGBT individuals is regularly under-reported. Attempts to control for that under-reporting have shown up to 19% of the U.S. population experience same-sex attraction,6 although more traditional methodologies suggest around 11%.7\nIt’s possible that the useR! survey is one of the surveys in which under-reporting is found - although 447 responses were received, which suggests people at least didn’t skip it - but it’s probably fair to say that such a sizeable difference in outcome is going to contain some genuine differences in population, as well as methodological variation.\nAdditionally, it is probable that the other demographics of LGBT attendees reflect the overall demographics of attendees, meaning that (for example) we would expect to find lesbians or bisexual women under-represented in that 5%.\n\n\nAge\nApproximating age (by subtracting the year of birth from 2016) shows the following:\n\nWomen trend younger than men at the conference, but the age distribution is similar across the two genders; 47% of respondents (n = 438) were born in the 1980s - in other words, were people in their late 20s to mid 30s. This lines up neatly with the education data (more on that later) and suggests that people in their early 20s and 40+ year olds are not finding the conference appealing - because there are other things to spend time on, because money is tighter, or for some other reason.\nThe women-being-younger element suggests that the rise in women attending (compared to 2015, where the proportion of women was only 19%) represents younger or newer members of the community attending, too.\n\n\nGeography\nThe R community is a highly international one, with developers in a wide range of countries. One of the things we were interested to discover is how this comes out in the attendee mix at useR!. Accordingly, we asked attendees which country they currently resided in.\nAltogether, R programmers from 34 nations attended useR!, but the overwhelming majority of respondents (71% of n = 443) live in the United States. In some ways this isn’t surprising - the cost of getting to Stanford increases the further away you are, and it’s expensive to start with! - and the rotation of the conference between continents each year means that many non-US R programmers are likely to simply attend the next European event. At the same time, it’s still somewhat disappointing for an event considered the “main” R conference, particularly with only ~20 attendees coming from Canada, a country bordering the U.S.\n\n\n\nEducation\nThe vast majority of attendees (>85%, of n = 451) had completed postgraduate degrees:\n\n\n\nHighest Qualification Completed\nWomen (%)\nMen (%)\n\n\n\n\nProfessional degree or certification\n1.2\n2.8\n\n\nDoctorate\n41.7\n45.7\n\n\nMasters degree\n42.9\n40.4\n\n\nUndergraduate degree\n13.7\n10.3\n\n\nHigh school/Secondary school or lower\n0.6\n0.7\n\n\n\nThis further suggests, on top of the data around age, that the conference is not attracting younger and more-early-career R programmers and researchers. Part of this may simply be that spending money on an R conference may be a lot easier to justify when you’re in full-time employment, or in a postgraduate degree with a stipend, than as an undergraduate or masters student; part of it is probably also that people without degrees, or without postgraduate degrees, earn less money and may come from poorer backgrounds, extending the problem.\nAt the same time, it is worth noting that the concept of research conferences as places to attend is not something particularly pushed on undergraduates, and so there is a component of awareness as well as finance. Finally, it may simply be that the conference is very academia-oriented, and so is particularly attractive to academics (and those familiar with academia) rather than R programmers without an academic background.\nAs the age data suggests, women tend to be slightly earlier on in the traditional academic career path.\n\n\nProfessional environment\nAlmost all of the attendees were employed, which (with the cost of the tickets) makes sense. More interestingly, a majority of the attendees (~57% of n = 444) were employed outside academia, primarily by private sector organisations. This is a strong indicator of what we’ve known anecdotally for a while - that R, a language originally designed and used in academia, is becoming more prevalent outside that context. At the same time, this may be a (somewhat) localised effect: while the language is increasingly popular, the technology industry centred on Silicon Valley is certainly an outlier in many respects for research overall.\n\nAnother interesting takeaway was that men are more likely to work in industry and permanent academic jobs than women - and women are far, far more likely to be students. Again, this isn’t surprising since it fits the pattern that women attending tend to be younger than men, and overall patterns that the tech industry (which is where one would expect the majority of privately-employed R programmers and scientists to work) has a known problem with employing and promoting women, as does academia.\nAlmost all attendees work full-time. It’s difficult to tell if this is due to the wider community largely being employed or engaged in full-time activities, or due to the cost of attendance diminishing the ability of community members in more economically fragile situations such as part-time work or unemployment to attend. Female attendees were less likely to work part-time, and far more likely to identify their status as unemployed (although the sample size is too small to really draw conclusions):\n\n\n\nEmployment Status\nWomen (%)\nMen (%)\n\n\n\n\nFull-time\n92.2\n94.3\n\n\nPart-time\n1.8\n4.3\n\n\nI am not currently employed\n6.0\n1.4\n\n\n\nThe proportion identifying as unemployed is greater than the proportion that previously identified as unemployed or retired, which could indicate that some students are categorising themselves as ‘not in employment’ when not presented with an option that reflects student-status.\n\n\nCaregiving\nApproximately a quarter of respondents answered “yes” to the question “are you a caregiver for children or adult dependents on a regular basis?” (n = 445). More men than women identified as caregivers. This either indicates that R programmers are a singularly socially enlightened population, or reflects wider sociological conditioning around caregiving which makes it easier for men to leave children at home with their partner (if applicable) than for women to do the same - resulting in a self-selection effect in which women with children are less likely to be able to attend (and so women who do attend are less likely to have children they care for).\nQualitative data suggests, unsurprisingly, the latter - in the free-text field for the survey, several (female) respondents mentioned the difficulty of persuading their (male) partners to handle childcare to allow them to attend conferences.\n\n\n\nCaregiving Status\nWomen (%)\nMen (%)\n\n\n\n\nNo\n78.3\n71.2\n\n\nYes\n21.7\n28.8" }, { - "objectID": "blog/2019/the-state-of-r-in-africa/index.html#the-future", - "href": "blog/2019/the-state-of-r-in-africa/index.html#the-future", - "title": "The state of R in Africa", - "section": "The Future", - "text": "The Future\nR as a statistical programming language has a great value to the data science community on the continent and useRs are showing this value through their work, research and education. Most useR groups in Africa currently focus on developing material that shows the amazing facets of R, rendering it as an option on the table for potential clients and the community. We are starting to see R cross paths with other programming languages thus raising a need to create room for it in learning and early career choices through building communities, mentoring talent and eventually powering businesses. Follow AfricaR and individual chapters on their social media to view the most recent updates on events." + "objectID": "blog/2017/mapping-users/index.html#recommendations", + "href": "blog/2017/mapping-users/index.html#recommendations", + "title": "Mapping useRs", + "section": "Recommendations", + "text": "Recommendations\n\nConference proposals\nThe survey data surfaces a lot of problems that can be tackled directly by future useR! conferences, and other conferences in the field too. In particular, it shows that while the gender breakdown of the conference is not as bad as we might fear, it’s still lagging behind the general population of the scientific fields R programming draws from, as well as the population as a whole. In addition, and in some ways more worryingly, attendees are overwhelmingly white, with Native Americans, Latinx people and people of African descent particularly under-represented.\nThese problems won’t be solved overnight, but there are several things the conference can do that would make attending a more viable and enjoyable prospect for under-represented groups. These include:\n\nA wider scholarship system. useR! 2016 featured scholarships, helping pay for things like plane tickets or hotels for people from marginalised backgrounds who wished to attend. The committee tasked with allotting the money did excellent work, but the money available was small. Expanding the scholarship fund in future conferences would let more under-represented R programmers attend, going a long way towards making a more representative conference.\nChildcare and feeding support. One of the things we saw in qualitative data, and something the quantitative data points to, is that the difficulties of juggling childcare is a blocker on attendance, particularly for women. Providing subsidised or free childcare at the conference itself (along with breastfeeding rooms), and incorporating childcare into the scholarship system, would help with this, and has been successfully done elsewhere.8\nStaggered ticket release. useR! 2016 sold out incredibly quickly, with all of the tickets gone within a day. This made it difficult for people to attend if they weren’t extremely on the ball and able to decide, on or before the first registration day, that they wanted to attend. By definition this hurts marginalised people because it hurts people who, for financial reasons, need to put some energy behind working out if they can attend. One solution worth considering is staggering the release of tickets over several days or weeks - perhaps with a waiting or notification list. This offers potential attendees multiple opportunities, reducing the penalty paid for not being ready to go on day 1.\nA more precise code of conduct. Following an open letter in 2015 the R Foundation adopted a resolution that any Foundation-affiliated conference have a Code of Conduct,9 which we applaud. What that code contains, however, in terms of restrictions, the amount of information given to attendees, and the enforcement mechanisms and their ease of use, is largely left up to the individual conference instance. This creates inconsistency and uncertainty for both attendees and conference organisers. Selecting a specific code of conduct, with a specific enforcement mechanism, along with training for enforcers, would solve for much of this, and give concerned attendees more certainty that the conference is a safe place to be.\n\n\n\nTask Force proposals\nThis survey has also helped to shape the goals of the Task Force on Women in the R Community. In particular, focusing in women, as a catchall, is not enough. Issues such as race, sexuality, disability and class intersect with gender and must also be considered if we are to build an R community that is more representative of the scientific/software communities and of society as a whole.\nAccordingly we are rebranding the Task Force as simply Forwards, so that we can consider the needs of other marginalised groups as part of our mission. Our primary focus will still be on women as there remains much work to do here and broadening participation of women was the motivation for setting up the task force. However many of the practical actions we can take, such as the proposals above, will also impact other marginalised groups and making this impact a formal part of our mission will help to ensure our actions do not only benefit white, highly educated women.\nAs an immediate consequence, we will be publishing an open call for participation, seeking more members for the group. We are particularly interested in talking to volunteers from non-White, LGBT, non-middle-class or early career backgrounds.\nRunning this survey has also served to reinforce that we have no fundamental ground truth here; it is hard to see what the backgrounds of those who try but fail to attend useR are, and their reasons for not going - it is hard to see what the demographics of R community members overall look like. Accordingly we will be running further surveys, adjusting several questions to factor in things we’ve learned from running this one, looking at the overall community and useR! attendees in a more nuanced way." }, { - "objectID": "blog/2020/blacklivesmatter-statement/index.html", - "href": "blog/2020/blacklivesmatter-statement/index.html", - "title": "#BlackLivesMatter: A joint statement by Forwards and R-Ladies", - "section": "", - "text": "As organizations committed to broadening diversity and inclusion in our community, we stand with #BlackLivesMatter and join those who demand justice for systemic oppression. Pervasive racism negatively impacts the participation of Black people in society. The current events in the USA echo what has happened and continues to happen to minoritised people across the world. We are aggregating resources and are taking deliberate actions to amplify the voices of Black, Indigenous and People of Color in the R community now and moving forward.\nTo our community members who are suffering right now, we stand by you, we hear your voices, but we know that that is not enough to enact the change we need. The work of breaking systems of injustice is slow and hard, and we know that some of you are carrying more of the load than others. There are no words to make this easier." + "objectID": "blog/2017/mapping-users/index.html#notes", + "href": "blog/2017/mapping-users/index.html#notes", + "title": "Mapping useRs", + "section": "Notes", + "text": "Notes\nIf your company would like to sponsor diversity scholarships or childcare at useR! 2017, please contact the chair of the local organizing committee, Tobias Verbeke (%20tobias.verbeke at openanalytics dot eu).\nWe do not plan to release the raw survey data as many individuals can be uniquely identified from one or two demographic questions. We may release the data in an aggregated form once we have completed our full analysis (this post covers the first of three sections).\nThe analysis presented here used the following packages:\n\nFor data manipulation: dplyr, forcats, maptools, matrixStats, tidyr\nFor visualisaton and reporting: knitr, ggplot2, mapproj, RColorBrewer, rworldmap, scales\n\nThe code is available in the Rmarkdown file." }, { - "objectID": "blog/2020/blacklivesmatter-statement/index.html#a-message-from-forwards", - "href": "blog/2020/blacklivesmatter-statement/index.html#a-message-from-forwards", - "title": "#BlackLivesMatter: A joint statement by Forwards and R-Ladies", - "section": "A Message from Forwards", - "text": "A Message from Forwards\nForwards recognizes that Black people are often missing or overlooked in core activities of the R community. We acknowledge that many are frustrated by the slow progress or apparent lack of action. At a time when we are reminded that racial injustice pulls people down, it is our goal to create space for Black, Indigenous and People of Color to rise as R programmers and community leaders.\nWe work through small, but hopefully impactful actions, such as:\n\nHighlighting the work of people from underrepresented groups and sharing information about relevant events and opportunities on @R_Forwards Twitter.\nSupporting useR! conference organizers with the diversity scholarship program.\nRecommending people from underrepresented groups for roles such as conference speakers, committee members, session chairs, etc.\nSupporting the leadership team of AfricaR.\nReaching a diverse group with our workshops for women and girls and workshops in underserved regions (e.g. Cuba, Southern Africa).\n\nWe understand that there is much more that could be done to directly support and represent Black, Indigenous and People of Color and we are committed to play our part. We will continue to develop actions and long-term goals to improve intersectional representation in our taskforce and the wider R community." + "objectID": "blog/2017/mapping-users/index.html#footnotes", + "href": "blog/2017/mapping-users/index.html#footnotes", + "title": "Mapping useRs", + "section": "Footnotes", + "text": "Footnotes\n\n\nSee our supplementary report Non-Responses in the UseR! 2016 Survey↩︎\nNational Science Foundation (2013) Women, Minorities, and Persons with Disabilities in Science and Engineering↩︎\nLandivar (2013) Disparities in STEM Employment by Sex, Race, and Hispanic Origin↩︎\nNative Americans are technically overrepresented, but given we’re talking about single digits of attendees here that probably isn’t meaningful - see CEOSE (2012) Biennial Report to Congress↩︎\nUnited States Census↩︎\nCoffman (2013) The Size of the LGBT Population and the Magnitude of Anti-Gay Sentiment are Substantially Underestimated↩︎\nGates (2011) http://williamsinstitute.law.ucla.edu/research/census-lgbt-demographics-studies/how-many-people-are-lesbian-gay-bisexual-and-transgender/↩︎\nBrown (2014) PyCon 2014: Community, community, community. Also, childcare.↩︎\nR Foundation (2015) https://www.r-project.org/behaviour.html↩︎" }, { - "objectID": "blog/2020/blacklivesmatter-statement/index.html#a-message-from-r-ladies", - "href": "blog/2020/blacklivesmatter-statement/index.html#a-message-from-r-ladies", - "title": "#BlackLivesMatter: A joint statement by Forwards and R-Ladies", - "section": "A Message from R-Ladies", - "text": "A Message from R-Ladies\nWhile the R-Ladies mission is focused on improving gender diversity within the R community, we also recognize both the struggle that Black people face, and the compound effect of intersectionality when a member identifies with multiple underrepresented groups. R-Ladies Global makes a commitment to improve how the organization supports Black, Indigenous and People of Color through the following actions:\n\nWe will start and continue dialogue around concrete actions to promote social justice globally through dedicated channels in our Slack workspaces. As we engage, we commit to listening, empathizing, seeking to understand, and translating our conversations into action. We commit to making our community spaces places of not only safety for all our members, but of active work towards equity and justice.\nWe will incorporate into our website a dedicated page of resources and information regarding tangible actions we, as an organisation, and single individuals can take to support #BlackLivesMatter and other social justice movements.\nWe will improve ethnic and racial representation on the R-Ladies Global Team so voices from all intersectional minorities are better represented.\nWe will launch a number of programs to support our members (e.g. travel grants, book vouchers, educational subscriptions) through funds donated to R-Ladies, we will dedicate 50% of the funds towards community members with intersectional identities and half of that directed exclusively to Black members." + "objectID": "blog/2017/users-participation-in-the-r-community/index.html", + "href": "blog/2017/users-participation-in-the-r-community/index.html", + "title": "useRs Participation in the R Community", + "section": "", + "text": "In our first and second posts on the useR! 2016 survey we discussed the responses from the demographic and programming sections. The main findings were:\nIn this last blog post of the series, we consider useRs involvement in the wider R community." }, { - "objectID": "blog/2020/blacklivesmatter-statement/index.html#closing-statement", - "href": "blog/2020/blacklivesmatter-statement/index.html#closing-statement", - "title": "#BlackLivesMatter: A joint statement by Forwards and R-Ladies", - "section": "Closing statement", - "text": "Closing statement\nWe will work harder to listen to and amplify the voices of minoritized members of our respective communities worldwide. We are invested in the continuous work of breaking down systems of injustice, and in making room for those that are currently suffering in those systems to participate fully and occupy leading positions. We urge everyone in the R community to do the same.\nR Forwards Core Team: Heather Turner, Noa Tamir, Tatjana Kecojevic, Emily Dodwell, Kevin O’Brien, Julie Josse.\nR-Ladies Global: Claudia Vitolo, Erin LeDell, Hannah Frick, Laura Ación, Athanasia Monika Mowinckel, Yanina Bellini Saibene, Noa Tamir, Maëlle Salmon, Jennifer Thompson, Florencia D’Andrea, Patricia A. Loto, Saranjeet Kaur Bhogal, Christin Zasada, Nadejda Sero, Sheila Saia.\nR-Ladies chapter organizers (current and former) with others strongly involved in the R-Ladies and R communities: gwynn sturdevant, Paola Corrales, Paloma Rojas-Saunero, Riva Quiroga, Roxana Noelia Villafañe, Monica L. Alonso, Danielle Navarro, Mine Çetinkaya-Rundel, Sara Mortara, Genelle Denzin, Divya Seernani, Elisa Schneider, Kyla McConnel, Ana Laura Diedrichs, Liza Dosso, Mariel Lovatto, María Nanton, Ludmila Janda, Hazel Kavili, Ines Teacã, Lucía Rodríguez Planes, Andrea Sánchez-Tapia, Disha Patil, Ayanthi Gunawardana, Jan Strappa, Kaelen Medeiros, Vebashini Naidoo, Emily Dodwell, Julia Silge, Marcela Alfaro, Jenny Bryan, Lucy D’Agostino McGowan, Alison Hill, Andrea Gómez Vargas, Angela Li, Beatriz Milz, Haydée Svab, Tijana Blagojev, Katarina Kosmina, Jovana Savic." + "objectID": "blog/2017/users-participation-in-the-r-community/index.html#summary", + "href": "blog/2017/users-participation-in-the-r-community/index.html#summary", + "title": "useRs Participation in the R Community", + "section": "Summary", + "text": "Summary\nA large proportion of useR! attendees feel that they belong to the R community, with the proportion increasing with length of time using R.\nStackoverflow and the R mailing lists are the most common resources used for support, despite the negative experience of some useRs. A third of useRs attend a local user group, although the proportion is higher among men than women. The main reasons for not attending are there is no group nearby, or people are too busy. The top initiatives that would encourage more involvement are a new user group nearby and mentoring. Women are more likely than men to want additional support and are more in favour of online support and initiatives targeted at their demographic.\nThe respondents had many suggestions for improving the R community and these along with the other survey responses provide a basis for Forwards and other R community leaders to work towards greater engagement." }, { - "objectID": "conferences.html", - "href": "conferences.html", - "title": "Conferences", - "section": "", - "text": "Forwards works to promote diversity and inclusion at R community conferences, especially useR!, the main R conference organized by the R Foundation.\nIn 2016 we made a series of recommendations, which have led to many improvements\n\nincreased representation of women in invited roles (speakers, program committee, session chairs)\nincreased representation of women in contributed program and attendees\nnewcomer-focused sessions since 2017 (excluding 2020 due switching to a virtual event)\ndiversity scholarships since 2016\nchildcare since 2017\ncode of conduct from 2016, with standard code of conduct adopted in 2020\n\nMore recently, we have been focusing on global representation and accessibility for people with disabilities." + "objectID": "blog/2017/users-participation-in-the-r-community/index.html#survey-results", + "href": "blog/2017/users-participation-in-the-r-community/index.html#survey-results", + "title": "useRs Participation in the R Community", + "section": "Survey results", + "text": "Survey results\n\nBelonging to the Community\nThe first question asked useRs whether they considered themselves to be part of the R community: 361 (79%) said yes, 69 (15%) said no and 28 (6%) did not give an answer. There was no significant difference in responses from men and women.\nIt’s encouraging that such a large proportion feel part of the R community: as might be expected the proportion increased with the length of time the respondent had used R, yet even people with less than 6 months’ experience responded positively. This is a testament to a generally welcoming community as backed up by some of the free text comments, for example:\n\nY’all seem to have a very active and robust community - keep it up!" }, { - "objectID": "data.html", - "href": "data.html", - "title": "Data", - "section": "", - "text": "The survey sub-team is focused on monitoring diversity and exploring obstacles, motivations, and involvement of useRs in the community. Diversity will be monitored via basic demographic summaries from specifically designed surveys or other community surveys (e.g. useR! feedback survey).\n\n\n\nThe taskforce collates data on the gender breakdown and other demographics of contributors to the R project, particularly R Foundation supported activities. For many of the gender summaries the gender was predicted based on first name, giving a rough approximation that assumes binary gender categories." + "objectID": "blog/2017/users-participation-in-the-r-community/index.html#conclusions", + "href": "blog/2017/users-participation-in-the-r-community/index.html#conclusions", + "title": "useRs Participation in the R Community", + "section": "Conclusions", + "text": "Conclusions\nIt has taken us a while to work through the survey and report back. However a benefit of this is we can see that actions in the meantime by Forwards and the wider community are already starting to address many of the issues raised in the last part of the survey.\nThe massive expansion of R-Ladies over the past year (from 4 groups to over 452) means that many people who were looking for a group now have one nearby, or will have soon. Many of the suggestions for useR! are in place for useR! 2017: there will be a newbies session, childcare and a “hackathon space” for informal birds of a feather gatherings. In addition 26 participants were awarded diversity scholarships (thanks to the conference sponsors, especially platinum sponsors Microsoft, Open Analytics, R Consortium, RStudio, DataCamp, and IBM).\nWith regards to education and outreach, the Forwards Teaching sub-team were recently awarded an R Consortium grant to develop workshops specifically targeting women and high school girls - initial workshops are planned for September and December in Melbourne, Australia and Auckland, New Zealand respectively. Further workshops will be run in Europe and the US, and the material made available under a Creative Commons share-alike license for others to use.\nBeyond this, we can use the ideas and findings here to inform future initiatives. For example the Forwards Community sub-team can help to promote local groups by raising awareness, connecting people that want to start new groups and sharing ideas to increase participation. In line with our mission to increase participation among under-represented groups, we can focus on initiatives that appear to be particularly appealing to women, such as mentoring and an online forum.\nOverall we have learnt a lot from our survey of useR! participants. In future we would like to study other populations and have package authors in mind for our next big survey. However, we still wish to monitor participation of under-represented groups at useR! so will be running a demographic survey as part of the general conference evaluation survey at useR! 2017. If you’re coming to useR! please support us by responding!" }, { - "objectID": "data.html#overview", - "href": "data.html#overview", - "title": "Data", - "section": "", - "text": "The survey sub-team is focused on monitoring diversity and exploring obstacles, motivations, and involvement of useRs in the community. Diversity will be monitored via basic demographic summaries from specifically designed surveys or other community surveys (e.g. useR! feedback survey).\n\n\n\nThe taskforce collates data on the gender breakdown and other demographics of contributors to the R project, particularly R Foundation supported activities. For many of the gender summaries the gender was predicted based on first name, giving a rough approximation that assumes binary gender categories." + "objectID": "blog/2017/users-participation-in-the-r-community/index.html#notes", + "href": "blog/2017/users-participation-in-the-r-community/index.html#notes", + "title": "useRs Participation in the R Community", + "section": "Notes", + "text": "Notes\nNow that we have completed this blog series, we will work on preparing an aggregated data set that minimises the risk of disclosure. We hope to release this over the summer.\nThe analysis presented here used the following packages:\n\nFor data manipulation: dplyr, forcats, tidyr\nFor visualization and reporting: knitr, ggplot2\n\nThe code is available in the Rmarkdown file.\nThe banner photo was taken at useR! 2016 by Thomas Petzoldt, used with permission." }, { - "objectID": "data.html#packages", - "href": "data.html#packages", - "title": "Data", - "section": "Packages", - "text": "Packages\n\nMaintainer Demographics 2017\nIn Pinto, Wiese & Dias (2018). How Do Scientists Develop Scientific Software? An External Replication, the authors surveyed CRAN maintainers that self-identified as a scientist. The survey was conducted starting in late November 2017 and ending in early January 2018. The respondents were contacted by email and asked to complete an online questionnaire, with a response rate of 24% (a total of 1,553 responses).\n\nIn 2017, 11.0% of package maintainers who self-identified as scientists were women or non-binary.\n\n\n44.6% of respondents self-identified between 30 and 40 years of age at the time of the survey.\nOverwhelmingly, 80.0% of respondents self-identified as either having a completed or in-progress doctorate degree.\n16.5% of the respondents self-identified as being located outside of Europe and North America.\n\n\n\n\n\n\n\n\n\n\n\n\n\nAuthor Demographics 2010\nMair, P., Hofmann, E., Gruber, K., Hatzinger, R., Zeleis, A. and Hornik, K. (2015) Motivation, values, and work design as drivers of participation in the R open source project for statistical computing, PNAS describes the feedback from 1087 R package authors. The survey was conducted in 2010. Package authors were contacted by email and asked to complete a web form, with a response rate of 27%.\n\nIn 2010, 9% of package authors were women.\n\n\nThe 95% confidence interval for the proportion of women package authors in 2010 is 7.1-11.0%.\n32.5% of authors are from the USA, but they are distributed across the globe, including Indonesia, Kenya, Slovenia and Singapore.\nThe average package author was almost 39 years old, 50% of authors are between 30 and 45, and the youngest was 20." + "objectID": "blog/2017/users-participation-in-the-r-community/index.html#footnotes", + "href": "blog/2017/users-participation-in-the-r-community/index.html#footnotes", + "title": "useRs Participation in the R Community", + "section": "Footnotes", + "text": "Footnotes\n\n\nSee our supplementary report: useR! 2016 participants and the R community: a multivariate analysis.↩︎\nR-Ladies Global Community and Vision, Gabriela de Queiroz, Cascadia R Conference, June 3, 2017, Portland, OR.↩︎" }, { - "objectID": "data.html#conferences", - "href": "data.html#conferences", - "title": "Data", - "section": "Conferences", - "text": "Conferences\nData is being collated on past useR! conferences, the plots below show the data gathered so far.\n\n\n2016 saw a rise in the proportion of female attendees from 19% to 28%.\n\nThe proportion of contributed presentations is similar to the proportion of female attendees, showing that women are as likely to contribute and have their contributions accepted as their male counterparts. There was a greater increase in poster contributions from women than lightning or regular talks in 2016, which perhaps reflects a lower level of experience among the newcomers.\nPlot c shows groups that are more heavily selected. The numbers of female invited speakers has increased from zero in the early years (2004-2008) through one in later years (2009-2013) to two in recent years - this is the level that useR! is seeking to maintain for now. The number of tutorials with a female tutor was decreasing since 2007, but went up again to 1/3 in 2016. This is the target for 2017. useR! does not always have panel sessions, but apart from a panel in 2014 on women in the R community, women have been poorly represented. This is something useR! plans to address in any future panels.\nThe last plot shows invited organisational roles. Data on session chairs is only available for a few years, but recently the proportion of women has been similar that of attendees. The proportion of female committee members has been slowly rising to parity over the history of useR! (with an unusual high in 2007 when Di Cook, a taskforce member was a key organiser). The make-up of the local organising committee is much more variable, partly because the size of the committee changes a lot according to local needs. In recent years the proportion of women on the committee has been similar to or greater than that of attendees." + "objectID": "blog/2018/havanar/index.html", + "href": "blog/2018/havanar/index.html", + "title": "HavanaR Workshop 2018", + "section": "", + "text": "The first meeting of R users in Cuba, HavanaR! Club 2018, will take place from 29-10-2018 to 02-11-2018. The workshop is organized jointly by the Group of Probability and Statistics of Universidad de La Habana, the >eR-Biostat initiative, the Center for Statistics, CenStat & I-Biostat, Hasselt University, Belgium and Forwards.\nThe workshop will focus on visualisation methods and exploratory analysis of high dimensional and multivariate datasets.\nProgram:\n29-Oct: Basic concepts of exploratory data analysis using R. Exploratory Analysis of high dimensional data using R (Adetayo Kasim, Durham University, UK, a.s.kasim@durham.ac.uk and Ziv Shkedy, Hasselt University, Belgium, ziv.shkedy@uhasselt.be).\n30-Oct: Exploratory Analysis of high dimensional data using R (Adetayo Kasim and Ziv Shkedy).\n31-Oct: HavanaR! Club 2018: The Cuban R users workshop with presentations of the participants.\n01-Nov: Exploratory Multivariate Data Analysis using R (Julie Josse, Ecole Polytechnique, France, julie.josse@polytechnique.edu).\n02-Nov: Exploratory Multivariate Data Analysis using R (Julie Josse).\nThe workshop is free but registration in mandatory. To register please send an email to erbiostat@gmail.com or cbouza2002@gmail.com.\nMore details and workshop materials will be available online at https://er-biostat.github.io/Courses/. All updates about the workshop will be anounced on the Facebook page (https://www.facebook.com/ER-BioStat-1463845487001786/) and Twitter (@erbiostat).\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" }, { - "objectID": "docs/MCA_programming_useR2016_survey/index.html", - "href": "docs/MCA_programming_useR2016_survey/index.html", - "title": "useR! 2016 participants and R programming: a multivariate analysis", + "objectID": "blog/2019/rladies-charlottesville-workshop-recap/index.html", + "href": "blog/2019/rladies-charlottesville-workshop-recap/index.html", + "title": "Recap of R-Ladies Charlottesville Forwards Workshop", "section": "", - "text": "The useR! survey gathers responses to questions on different themes for 455 attendees: demographic characteristics, R programming and involvement in the R community. The separate analyses of each question in each theme are detailed in the posts Mapping useRs, useRs Relationship with R and Community Involvement of useRs. Here, we aim at understanding attendees’ joint responses to the questions of the survey for a given theme. In other words, we would like to highlight the relationships between their answers, as well as to highlight the similarities between the respondents. Multiple correspondence analysis (MCA) is a dimensionality reduction method which allows to explore and visualize a set of categorical variables. It can be seen as the counterpart of PCA for categorical data. The aim of this document is to go beyond univariate analyses and to present the results of a multivariate analyses of the R programming questions using MCA. A corresponding analysis of the R community questions is detailed in a companion report.\n\n\n\nWe base our study on the following questions:\n\n\n\nQ1 What did you register as at useR! 2016?\nQ2 What is your gender?\nQ3 In what year were you born?\nQ4 To what racial or ethnic group(s) do you identify?\nQ5 In what country do you currently reside?\nQ6 Do you identify as LGBT (Lesbian, Gay, Bisexual, Asexual and/or Transgender)?\nQ7 What is the highest level of education you have completed?\nQ8 What is your current (primary) employment status?\nQ9 Is your current job full-time or part-time?\nQ10 Are you a caregiver for children or adult dependents on a regular basis?\n\n\n\n\n\nQ11 How long have you been using R for?\nQ12 Did you have previous programming experience before beginning to use R?\nQ13 Which of the following do you do? Tick any that apply among\n\nQ13A I use functions from existing R packages to analyze data\nQ13B I write R code designed to make my work easier, such as loops or conditionals or functions\nQ13C I write R functions for use by myself or my collaborators\nQ13D I contribute to R packages (on CRAN or elsewhere)\nQ13E I have written my own R package\nQ13F I have written my own R package and released it on CRAN or Bioconductor (or shared it on GitHub, R-Forge or similar platforms)\n\nQ14 Do you use R as a recreational activity, primarily as part of a job or both?\nQ15 How much do you agree or disagree with the following statements?\n\nQ15A Writing R is fun\nQ15B Writing R is considered cool or interesting by my peers?\nQ15C Writing R is a monotonous task\nQ15D Writing R is difficult\n\nQ16 Would you recommend R to friends or colleagues as a programming language to learn?\nQ17 What would be your number one argument for/against learning R?\n\nQuestions Q1-Q10 focus on the demographic characteristics of the respondents while questions Q11, Q13 and Q14 are related to the use of R, and questions Q15 to Q17 to the perception of R. Note that Q12 is about programming in general and not specifically dedicated to R.\nWe first focus on the topic “uses of R” and we will consider the perception questions in a second step. The demographic questions are also used in the analysis in order to help in the interpretation and to describe the profile of R programming answers.\n\n\n\n\nQuestions Q1, Q5 and Q17 have a category of answer Other (please specify). The “free” answers have been gathered in different categories and included as new categories in the questions. The new variables (with more levels) are named Q1_new, Q5_new and Q17_new. In addition, some categories name have been modified to make them easily understandable.\nNote that questions Q13_A to Q13_F are answered by ticking one box indicating that the respondent agrees with the category. Consequently, if a box is unchecked, it is impossible to know if they disagree or if they don’t answer the question. Such responses are recoded as yes if the box is checked and recoded as no otherwise." + "text": "On September 8, 2019, Samantha Toet and Angela Li co-taught a 3-hour Forwards Package Development Workshop at a weekend R-Ladies Charlottesville Meetup.\nThe workshop took place as a result of Angela being in town - she reached out to Sam and suggested the workshop, Sam thought it was a good idea, and they worked together to coordinate the logistics (all Sam!) and teaching. By using the Forwards curriculum and pre-made organizing templates - with a few tweaks of their own, of course - they were able to pull together the workshop in a month.\nThe workshop was an abbreviated version of the full Forwards curriculum that allowed participants to develop their first-ever package. The workshop started with motivating the need to create a package, then walked through making a package from scratch, then went over best practices and sharing out a package. We thought it was a good “story arc” for participants: create, document, test, and share.\nWe enjoyed teaching the workshop, and there were several things we learned from teaching it:\n\nLet them eat cake (first), or have participants create and explore their own package, no matter how small it is. You can help with some of the heavy lifting by providing sample functions to use in the package, but give them ownership of the full process.\nMistakes are good! Coding is never perfect or streamlined, so by troubleshooting on the spot, you’re demonstrating the iterative process. For example, Sam started off her session by live troubleshooting a Roxygen tagging issue. Participants could call out their suggestions and collaboratively come to a solution. Participants were also able to get a real taste of the process of looking at help pages, changing some part of the code, re-documenting and building the package, and looking at the results.\nFocus on workflows and process over exact tooling. The goal of this workshop was not to make every participant an expert package developer, but help participants see the patterns of package development. By internalizing these patterns (for example, modify code -> load -> explore in console, or write tests -> modify code -> load), participants are able to understand the general workflow and start to ask deeper questions and explore more on their own.\n\nIf you’re interested in organizing an R-Ladies based workshop of your own, you can use the resources we developed. Please don’t hesitate to reach out to either of us for more information - we’d be happy to chat (or maybe even co-teach)!\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" }, { - "objectID": "docs/MCA_programming_useR2016_survey/index.html#introduction", - "href": "docs/MCA_programming_useR2016_survey/index.html#introduction", - "title": "useR! 2016 participants and R programming: a multivariate analysis", + "objectID": "blog/2019/workshops-for-women-and-girls/index.html", + "href": "blog/2019/workshops-for-women-and-girls/index.html", + "title": "Workshops for Women and Girls", "section": "", - "text": "The useR! survey gathers responses to questions on different themes for 455 attendees: demographic characteristics, R programming and involvement in the R community. The separate analyses of each question in each theme are detailed in the posts Mapping useRs, useRs Relationship with R and Community Involvement of useRs. Here, we aim at understanding attendees’ joint responses to the questions of the survey for a given theme. In other words, we would like to highlight the relationships between their answers, as well as to highlight the similarities between the respondents. Multiple correspondence analysis (MCA) is a dimensionality reduction method which allows to explore and visualize a set of categorical variables. It can be seen as the counterpart of PCA for categorical data. The aim of this document is to go beyond univariate analyses and to present the results of a multivariate analyses of the R programming questions using MCA. A corresponding analysis of the R community questions is detailed in a companion report.\n\n\n\nWe base our study on the following questions:\n\n\n\nQ1 What did you register as at useR! 2016?\nQ2 What is your gender?\nQ3 In what year were you born?\nQ4 To what racial or ethnic group(s) do you identify?\nQ5 In what country do you currently reside?\nQ6 Do you identify as LGBT (Lesbian, Gay, Bisexual, Asexual and/or Transgender)?\nQ7 What is the highest level of education you have completed?\nQ8 What is your current (primary) employment status?\nQ9 Is your current job full-time or part-time?\nQ10 Are you a caregiver for children or adult dependents on a regular basis?\n\n\n\n\n\nQ11 How long have you been using R for?\nQ12 Did you have previous programming experience before beginning to use R?\nQ13 Which of the following do you do? Tick any that apply among\n\nQ13A I use functions from existing R packages to analyze data\nQ13B I write R code designed to make my work easier, such as loops or conditionals or functions\nQ13C I write R functions for use by myself or my collaborators\nQ13D I contribute to R packages (on CRAN or elsewhere)\nQ13E I have written my own R package\nQ13F I have written my own R package and released it on CRAN or Bioconductor (or shared it on GitHub, R-Forge or similar platforms)\n\nQ14 Do you use R as a recreational activity, primarily as part of a job or both?\nQ15 How much do you agree or disagree with the following statements?\n\nQ15A Writing R is fun\nQ15B Writing R is considered cool or interesting by my peers?\nQ15C Writing R is a monotonous task\nQ15D Writing R is difficult\n\nQ16 Would you recommend R to friends or colleagues as a programming language to learn?\nQ17 What would be your number one argument for/against learning R?\n\nQuestions Q1-Q10 focus on the demographic characteristics of the respondents while questions Q11, Q13 and Q14 are related to the use of R, and questions Q15 to Q17 to the perception of R. Note that Q12 is about programming in general and not specifically dedicated to R.\nWe first focus on the topic “uses of R” and we will consider the perception questions in a second step. The demographic questions are also used in the analysis in order to help in the interpretation and to describe the profile of R programming answers.\n\n\n\n\nQuestions Q1, Q5 and Q17 have a category of answer Other (please specify). The “free” answers have been gathered in different categories and included as new categories in the questions. The new variables (with more levels) are named Q1_new, Q5_new and Q17_new. In addition, some categories name have been modified to make them easily understandable.\nNote that questions Q13_A to Q13_F are answered by ticking one box indicating that the respondent agrees with the category. Consequently, if a box is unchecked, it is impossible to know if they disagree or if they don’t answer the question. Such responses are recoded as yes if the box is checked and recoded as no otherwise." + "text": "Thanks to generous funding from the R Consortium, Forwards has offered a series of workshops around the world to support the development of coding skills and to increase the participation of women in the R community. In the last year and a half, more than 10 workshops have engaged more than 100 high school students and women in Australia, New Zealand, Europe and the USA. Information about our series of workshops for women and girls can be found on the Edu section of the Forwards website.\nHere we round up some of the highlights." }, { - "objectID": "docs/MCA_programming_useR2016_survey/index.html#analysis-of-the-uses-of-r", - "href": "docs/MCA_programming_useR2016_survey/index.html#analysis-of-the-uses-of-r", - "title": "useR! 2016 participants and R programming: a multivariate analysis", - "section": "Analysis of the uses of R", - "text": "Analysis of the uses of R\nThe following graphic summarizes relationships between the answers to the “uses of R” questions. To interpret the main dimensions of variability in the response profiles, we base our analysis on the proximities between categories. Two categories are close on the graph when individuals who have selected the first category also tend to take the other category.\n\nProximities between categories Q11.NA and Q14.NA indicate that people who did not answer Q11 (How long have you been using R for?) often did not answer Q14 (Do you use R as a recreational activity, primarily as part of a job or both?). However, it only concerns 16 individuals.\nWe can see on the graph a gradient which shows the relationship between the question Q11 related to the experience in R programming and the question Q13 related to the use of R, with people on the right, who have recently started using R, and people on the left, who have used R for a long time. In particular, the users with more than 10 years’ experience have already written their own package or contributed to packages, while people with less than 2 years’ experience haven’t. The gradient can be clearly interpreted and shows the progression in gaining new skills.\nThe beginners in R seem to be trying R during their free time. This is less true for experienced users who have probably gained their experience during their job. Note that beginners in R are very few among respondents (9 people with less than 6 months’ experience).\nThe graph of the individuals allows identification of the individuals located at the top right who do not answer some questions. These individuals did not answer any of the questions related to their use of R but answered the demographic questions. Interestingly, one of them indicated they just discovered R (in the text answer Q25). This explanation could also be valid for the other ones, explaining why they agree to participate to the study, yet only answer a few questions. This comment is in line with the previous graph, in which categories NA are on the right, which is the location of inexperienced users." + "objectID": "blog/2019/workshops-for-women-and-girls/index.html#auckland", + "href": "blog/2019/workshops-for-women-and-girls/index.html#auckland", + "title": "Workshops for Women and Girls", + "section": "Auckland", + "text": "Auckland\nForwards teamed up with the Auckland University Department of Statistics to offer two R workshops in December 2017, one day for women on package development and one day for girls on web app development. Hadley Wickham and Jenny Bryan developed course materials for the package development workshop, while Di Cook developed the materials for the girls’ workshop. Both sets of materials were released under Creative Commons licenses so that they could be reused and adapted for future workshops.\nSee the material for the girls’ workshop and two of the apps developed by the girls to explore New Zealand’s PISA standardised scores: Booknerd’s App and Zoe’s App." }, { - "objectID": "docs/MCA_programming_useR2016_survey/index.html#analysis-of-the-perception-of-the-r-programming-language", - "href": "docs/MCA_programming_useR2016_survey/index.html#analysis-of-the-perception-of-the-r-programming-language", - "title": "useR! 2016 participants and R programming: a multivariate analysis", - "section": "Analysis of the perception of the R programming language", - "text": "Analysis of the perception of the R programming language\n\nThe analysis of questions related to the perception of the R language (Q15, Q16, Q17) shows again that attendees who did not answer one question often did not answer others (1st dimension). More interestingly, the second dimension of the graph highlights that people thinking very strongly that R is monotonous also think that it is not fun, not cool, or even think R is poor. It highlights that among respondents there is a sub-population of people who do not appreciate R. However, it concerns around 10 individuals.\nInterestingly, these respondents tend to recommend R to a friend as a programming language to learn, so that they recognize some interest." + "objectID": "blog/2019/workshops-for-women-and-girls/index.html#budapest", + "href": "blog/2019/workshops-for-women-and-girls/index.html#budapest", + "title": "Workshops for Women and Girls", + "section": "Budapest", + "text": "Budapest\nUsing the material developed for Auckland, Isabella Gollini and Heather Turner ran a package development workshop for women at eRum 2018. Thanks to support from the R Consortium and the eRum conference, eight women were funded to attend the workshop and given free conference registration, with representatives from Denmark, Georgia, Germany, India, Sweden and the UK. Other eRum participants were also able to attend.\n\n\n\nWomen in group discussions at the Budapest package development workshop" }, { - "objectID": "docs/MCA_programming_useR2016_survey/index.html#perception-and-uses-of-r", - "href": "docs/MCA_programming_useR2016_survey/index.html#perception-and-uses-of-r", - "title": "useR! 2016 participants and R programming: a multivariate analysis", - "section": "Perception and uses of R", - "text": "Perception and uses of R\nDoes the perception of the R language differ according to the experience of the user? To answer this question, the perception variables are projected as supplementary variables on the graph obtained with the “uses of R” variables. Supplementary variables are not used to build the dimensions of variability, they are projected a posteriori and help for the interpretation.\n\nWe note that experienced users particularly appreciate R. They find that R is fun, not monotonous and they recommend to use it." + "objectID": "blog/2019/workshops-for-women-and-girls/index.html#new-york-city", + "href": "blog/2019/workshops-for-women-and-girls/index.html#new-york-city", + "title": "Workshops for Women and Girls", + "section": "New York City", + "text": "New York City\nEmily Dodwell and Joyce Robbins taught the first Forwards high school girls workshop in the United States in October 2018 at AT&T in New York City. Sixteen motivated, curious, and dedicated students worked diligently throughout a morning session to tackle an introduction to R, plots in ggplot2, Markdown, and manipulating data with dplyr. Breakout groups over a lunch of pizza and salad discussed careers in data science; volunteers shared their career trajectories, and students asked questions and shared their experiences in high school STEM courses and extracurricular activities.\nThe six-hour workshop culminated in an afternoon hackathon, the theme of which was transportation in and around NYC. Each pair of students chose one of three publicly available datasets—NYC Flights, Taxis, and CitiBike—to explore using the R skills they learned earlier in the day. They then gave a five-minute presentation highlighting visualizations they created that captured interesting behavior or answered questions they formulated.\nMany thanks to the volunteers from AT&T Labs Research, Cheryl Flynn and Ritwik Mitra, and from R-Ladies NYC, Soumya Kalra and Angeline Protacio.\n\n\n\nWorking photo at the New York City Forwards girls’ workshop" }, { - "objectID": "docs/MCA_programming_useR2016_survey/index.html#relationship-with-demographic", - "href": "docs/MCA_programming_useR2016_survey/index.html#relationship-with-demographic", - "title": "useR! 2016 participants and R programming: a multivariate analysis", - "section": "Relationship with demographic", - "text": "Relationship with demographic\n\nDemographic variables are also projected as supplementary variables. We excluded the ethnic group variable (Q4) and the country of residence variable (Q5) because of the large number of infrequent categories. The graph above shows that the demographic characteristics are significantly related to the user profiles. An analysis of variance with demographic variables as covariates, and the coordinates of the individuals on the dimensions as explanatory variables, has been performed1. The graph shows that people with a doctorate are more highly represented among advanced users. This also shows that men are more highly represented than women among the most advanced users. As stated in the post useRs Relationship with R, it could be explained by the fact that women tend to be younger, but here we note that the variable Age does not significantly explain the coordinates of the individuals on the graph. To get more insight into this possible confounding effect, we created a variable sex-age and represent it. The plot confirms that men are over-represented amongst the advanced users." + "objectID": "blog/2019/workshops-for-women-and-girls/index.html#chicago", + "href": "blog/2019/workshops-for-women-and-girls/index.html#chicago", + "title": "Workshops for Women and Girls", + "section": "Chicago", + "text": "Chicago\n\n\n\nGroup photo of women at the Chicago package development workshop\n\n\nAngela Li and Stephanie Kirmer, both of R-Ladies Chicago, organized a women’s package workshop in February 2019 for 30 women at the Center for Spatial Data Science in Chicago. This marked the first time an R-Ladies group had run the full package development workshop. The workshop brought women from 11 states in the US to freezing-cold Chicago to learn how to develop their first package. The workshop was preceded by an R-Ladies get-together with an R-Ladies purple cake, where workshop participants from out-of-town were able to get to know each other.\n\n\n\nGroup photo of women at the R-Ladies get-together behind a table with a large iced purple cake\n\n\nPre and post-survey results from the workshop can be found online (thank you, Stephanie, for putting this together!). For a more in-depth look at the event, Josephine Lukito and Florencia Mangini both wrote fantastic recaps of the workshop. You can also find tweets from the event under the hashtag #RForwardsChi on Twitter.\nThanks to the R Consortium, funding was provided for 9 women from California, Tennessee, New York, Wisconsin, and more to attend this workshop. Thanks also to Katherine Simeon, Ola Giwa, and Nichole Burke for being helpers at this event." }, { - "objectID": "docs/MCA_programming_useR2016_survey/index.html#similarities-between-respondents", - "href": "docs/MCA_programming_useR2016_survey/index.html#similarities-between-respondents", - "title": "useR! 2016 participants and R programming: a multivariate analysis", - "section": "Similarities between respondents", - "text": "Similarities between respondents\nThe participants are clustered according to their answers to the uses of R questions only (Q11, Q13, Q14). To do this, a hierarchical clustering is performed on K principal components of the MCA. The rationale is to improve the stability of the clustering by building it from denoised data.\nSeveral rules can be used to select the number of components used for the clustering. Here we choose 12 dimensions which corresponds to 95% of the projected inertia (variance) of the data.\n\nThe number of clusters is chosen according to the barplot of the inertia gains2 which suggests 3 clusters.\nHowever, since a cluster with non-respondents is expected, we consider 4 clusters to have a more interpretable clustering.\n\nThe first cluster located on the left represent the experienced users while the second cluster gathers the intermediate users and the third one the beginners. The fourth cluster is constituted with people who did not answer.\nThe size of each cluster is as follows:\n\n\n\n\n1\n2\n3\n4\n\n\n\n\nsize\n171\n260\n11\n13\n\n\n\ni.e. in terms of proportions:\n\n\n\n\n1\n2\n3\n4\n\n\n\n\nproportion\n0.38\n0.57\n0.02\n0.03\n\n\n\nWe now interpret the clusters.\n\nCluster 1\nTo help us describing the first cluster, we use statistical tests to compare the proportion of each category in the cluster versus the proportion in the population of the respondents. Of course, for variables that have been used to build the clusters (Q11, Q13, Q14), this test is only indicative, but for others (demographic questions or perception questions), the p.values can be interpreted.\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ13_F=rel_pkg_yes\n96.77\n87.72\n34.07\n< 2e-16\n\n\nQ13_D=ctb_pkg_yes\n88.37\n88.89\n37.80\n< 2e-16\n\n\nQ13_E=wrt_pkg_yes\n71.85\n100.00\n52.31\n< 2e-16\n\n\nQ13_C=wrt_func_yes\n42.93\n97.66\n85.49\n3.5e-10\n\n\nQ13_B=wrt_code_yes\n42.35\n97.08\n86.15\n1.4e-08\n\n\nQ2=Men\n46.64\n77.19\n62.20\n2.2e-07\n\n\nQ7=Doctorate\n50.75\n59.06\n43.74\n3.5e-07\n\n\nQ11=> 10 years\n57.14\n39.77\n26.15\n4.6e-07\n\n\nQ15=fun_Strongly agree\n49.54\n62.57\n47.47\n5.7e-07\n\n\nQ14=For both recreational and job/educational purposes.\n52.50\n49.12\n35.16\n1.7e-06\n\n\nQ1_new=Q1_new_Academic/Govt\n46.81\n51.46\n41.32\n0.00071\n\n\nQ8=Q8_Employed non-permanently in academia\n57.63\n19.88\n12.97\n0.00089\n\n\nQ8=Q8_Employed permanently in academia\n53.95\n23.98\n16.70\n0.00157\n\n\n\nThe table can be interpreted as follows:\n\nfirst row indicates that 96.77% of individuals that have released their own R package are in cluster 1; 87.72% of individuals in this cluster have released their own R package, and 34.07% of individuals in the population have released their own R package.\n\nrow 7 indicates that 50.75% of individuals with a doctorate are in this cluster; 59.06% of individuals in this cluster have a doctorate, and 43.74% of individuals in the population have a doctorate. We can reject at risk 3.47e-07 the null hypothesis the proportion of respondents with a doctorate in the first cluster is the same than the proportion in the population of the respondents. This first table only represents the results when the proportion in the cluster is larger than the proportion in the population.\n\nTo wrap-up, the tests results confirm that cluster 1 gathers experienced users. In this cluster, there is an over-representation of people with a doctorate, men, or people employed in academia. It is also a cluster where the proportion of people strongly seeing R programming as fun is large. In the same line, people in cluster 1 are more likely to use R for both recreational and job/educational purposes.\nThis second table represents the categories that are underrepresented in cluster 1.\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ13_F=rel_pkg_no\n7.00\n12.28\n65.93\n< 2e-16\n\n\nQ13_D=ctb_pkg_no\n6.71\n11.11\n62.20\n< 2e-16\n\n\nQ13_E=wrt_pkg_no\n0.00\n0.00\n47.69\n< 2e-16\n\n\nQ13_C=wrt_func_no\n6.06\n2.34\n14.51\n3.5e-10\n\n\nQ13_B=wrt_code_no\n7.94\n2.92\n13.85\n1.4e-08\n\n\nQ11=6-12 months\n0.00\n0.00\n6.37\n6.6e-07\n\n\nQ2=Women\n23.08\n22.81\n37.14\n6.6e-07\n\n\nQ1_new=Q1_new_Industry\n26.46\n29.24\n41.54\n3.3e-05\n\n\nQ8=Q8_Employed in industry\n26.23\n28.07\n40.22\n3.7e-05\n\n\nQ14=Q14.NA\n0.00\n0.00\n3.52\n0.00045\n\n\nQ11=1-2 years\n11.43\n2.34\n7.69\n0.00046\n\n\nQ7=Masters degree\n28.34\n30.99\n41.10\n0.00065\n\n\nQ14=Primarily as part of a job or educational course;\n31.64\n50.88\n60.44\n0.00131\n\n\nQ11=Q11.NA\n0.00\n0.00\n2.86\n0.00196\n\n\nQ5=United States\n32.91\n60.82\n69.45\n0.00217\n\n\n\nUS people are under-represented in cluster 1. We can imagine that only people deeply using R are motivated to go to the US for such a conference due to the costs.\n\n\nCluster 2\nCluster 2 can be described as a cluster of intermediate users who use R since 1-2 years or less, but more than 6 months. They use R functions, but don’t write their own functions or packages. They appreciate R, but use it primarily for their job. They are more employed in the industry. This cluster gathers more women, more undergraduate and master and people from the US.\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ13_F=rel_pkg_no\n85.33\n98.46\n65.93\n< 2e-16\n\n\nQ13_D=ctb_pkg_no\n85.51\n93.08\n62.20\n< 2e-16\n\n\nQ13_E=wrt_pkg_no\n89.86\n75.00\n47.69\n< 2e-16\n\n\nQ11=6-12 months\n100.00\n11.15\n6.37\n4.4e-08\n\n\nQ14=Primarily as part of a job or educational course;\n66.91\n70.77\n60.44\n2.2e-07\n\n\nQ2=Women\n71.60\n46.54\n37.14\n1.4e-06\n\n\nQ11=1-2 years\n88.57\n11.92\n7.69\n4.0e-05\n\n\nQ8=Q8_Employed in industry\n67.76\n47.69\n40.22\n0.00017\n\n\nQ1_new=Q1_new_Industry\n67.20\n48.85\n41.54\n0.00026\n\n\nQ15=fun_Agree\n67.20\n48.08\n40.88\n0.00031\n\n\nQ7=Masters degree\n66.31\n47.69\n41.10\n0.00096\n\n\nQ2Q3=20-28_Women\n79.07\n13.08\n9.45\n0.00185\n\n\nQ16=rcmd_Yes\n59.09\n95.00\n91.87\n0.00558\n\n\nQ2Q3=29-33_Women\n75.56\n13.08\n9.89\n0.00786\n\n\nQ5=United States\n61.08\n74.23\n69.45\n0.01118\n\n\nQ13=use_func_yes\n58.63\n95.38\n92.97\n0.02258\n\n\nQ7=Undergraduate degree\n71.15\n14.23\n11.43\n0.02953\n\n\nQ15_D=difficult_Disagree\n62.56\n50.77\n46.37\n0.03045\n\n\nQ2Q3=>58_Men\n80.00\n6.15\n4.40\n0.03401\n\n\nQ10=Caryng_resp_No\n60.18\n76.15\n72.31\n0.03569\n\n\n\n\n\nCluster 3\nCluster 3 gathers respondents with less than 6 months of experience in R. They do not have an opinion about the “fun” or “monotonous” nature of R. They use R in their free time and find that the main advantage of R is that it is an open source software. This cluster gather curious users discovering R in their free time. No demographic characteristics show-up in this group.\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ11=< 6 months\n100.00\n81.82\n1.98\n< 2e-16\n\n\nQ14=Primarily as a recreational activity, in your free time;\n100.00\n36.36\n0.88\n1.9e-07\n\n\nQ13_C=wrt_func_no\n12.12\n72.73\n14.51\n1.6e-05\n\n\nQ13_B=wrt_code_no\n11.11\n63.64\n13.85\n0.00016\n\n\nQ15=fun_No opinion\n13.33\n36.36\n6.59\n0.00400\n\n\nQ16=rcmd_No\n14.29\n27.27\n4.62\n0.01195\n\n\nQ15_C=monotonous_No opinion\n7.46\n45.45\n14.73\n0.01564\n\n\nQ4=Native American\n100.00\n9.09\n0.22\n0.02418\n\n\nQ17_new=Open source\n11.11\n27.27\n5.93\n0.02484\n\n\nQ13_E=wrt_pkg_no\n4.15\n81.82\n47.69\n0.02518\n\n\n\n\n\nCluster 4\nAs expected, cluster 4 not described in detail here is a cluster where individuals do not answer questions, or do not check boxes.\n\n\nTo sum-up\nThe respondents can be classified in 3 clusters according to their uses of R:\n\nThe experienced users (38%): they have an in depth knowledge of R programming, even creating their own package. They are mainly men, academic, with a doctorate\nThe intermediate users (57%): they mainly use functions from existing packages, but do not write their own functions. They are mainly women, people from industry, who are undergraduate or have a master degree. In addition, they are more likely from US.\nThe curious users (3%): they have discovered R very recently. They don’t have an opinion that is already formed. They appreciate the open source nature of R.\n\nA fourth cluster of people that didn’t answer the question could be considered. It represents 2% of individuals. They could be potential future users that didn’t have any experience in R at the moment to complete the questionnaire." + "objectID": "blog/2019/workshops-for-women-and-girls/index.html#brisbane", + "href": "blog/2019/workshops-for-women-and-girls/index.html#brisbane", + "title": "Workshops for Women and Girls", + "section": "Brisbane", + "text": "Brisbane\nForwards teamed up with ACEMS to organise the Brisbane Coding Workshop for Girls held at River City Labs (https://www.rivercitylabs.net) in March 2019. There were approximately 10 girls and 5 helpers. The girls worked on instructional material to get up and running with R and the tidyverse (https://ebsmonash.shinyapps.io/sunny_tutorial/) in the morning. After a pizza lunch, the girls experimented with developing their own shiny app. A theme for the afternoon was “break it, fix it, break it, fix it, …” to encourage experimenting and trying new things. The girls used data from the Atlas of Living Australia, on wildlife sightings around Brisbane, as the basis for the app. There is an R package to interface with this extraordinary data resource. For examples of the apps developed see Claudia’s App and Rachel’s App.\n\n\n\nThe view into River City Labs where the Brisbane girls coding workshop was held, with the girls and leaders chatting at the pizza lunch" }, { - "objectID": "docs/MCA_programming_useR2016_survey/index.html#conclusions", - "href": "docs/MCA_programming_useR2016_survey/index.html#conclusions", - "title": "useR! 2016 participants and R programming: a multivariate analysis", - "section": "Conclusions", - "text": "Conclusions\nMissing values often occur on all the R programming questions. One possible explanation backed-up by the free text answer of one individual and by the proximity to the inexperienced users, is that the values are missing because the participants do not program in R. If so, the deletion of missing individuals for subsequent analyses would reduce the scope of the analysis since the sample would be restricted to R users only. However, the cluster of individuals who do not answer these questions, do not answer any of the R community questions as well. Consequently, it can also be individuals who have started answering the questions and stopped before finishing. So we decide to delete this group for the other analyses.\n\nPractices of R are linked to the experience of the users. In particular, users with more than 10 years’ experience have already written their own package, while people with less than 2 years’ experience haven’t.\nA focus on the demographic characteristics of the participants highlights experienced users are more likely men than women, more likely from academia than from industry and more likely people with a doctorate than without. They often use R both for their job and for pleasure. Intermediate users use R for less than 2 years, they mainly use existing packages. Intermediate users are mainly women, people with undergraduate and master degrees and less men or people with doctoral degrees. Beginners are trying R during their free time.\nTo conclude, we should suggest using “yes” and “no” answers for the checkboxes to distinguish missing values from “no”. In addition, we should be cautious about over-interpretation and keep in mind that their is a strong age effect: there are many women who are young." + "objectID": "blog/2019/workshops-for-women-and-girls/index.html#resources", + "href": "blog/2019/workshops-for-women-and-girls/index.html#resources", + "title": "Workshops for Women and Girls", + "section": "Resources", + "text": "Resources\nMaterials for Forwards workshops can be found in our workshops repository. Additional materials can be found in the teaching_examples repository or linked from our Education page. All Forwards workshop materials are licensed with a Creative Commons license to encourage reuse by the community - please check the exact license on the material, in some cases, there is a restriction to non-commercial use.\nIf you are interested in organizing a workshop of your own, please take a look at the Template Forwards Workshop Google Drive for materials you can use to coordinate logistics for your workshop! This was put together by the Chicago workshop organizers and is something the teaching team plan to build on to support workshop organizers." }, { - "objectID": "docs/MCA_programming_useR2016_survey/index.html#footnotes", - "href": "docs/MCA_programming_useR2016_survey/index.html#footnotes", - "title": "useR! 2016 participants and R programming: a multivariate analysis", - "section": "Footnotes", - "text": "Footnotes\n\n\nFor more details about the use of analysis of variance to interpret the MCA graphs, see: Francois Husson, Jerome Pages, Sebastien Le. Exploratory Multivariate Analysis by Example Using R. CRC Press Taylor & Francis, pp.240, 2010, Chapman & Hall/CRC Computer Science & Data Analysis.↩︎\nFor more details about the classification based on principal components methods, see the reference above.↩︎" + "objectID": "blog/2020/southern-africa-project-2020/index.html", + "href": "blog/2020/southern-africa-project-2020/index.html", + "title": "Southern Africa Project 2020", + "section": "", + "text": "Using the satRday Johannesburg 2020 conference as a springboard, Forwards set up a project to help build the R community in Southern Africa. With funding from the Why R? Foundation, the R Consortium and a crowd-funding campaign, Forwards collaborated with local R users to run a series of training and community events in South Africa, Eswatini and Botswana. All the events promoted AfricaR, the pan-African network of R users, to help raise awareness of this community among R users in Southern Africa.\n\nSouth Africa\nThe events began with Heather Turner assisting Bianca Peterson in running her 2-day Introduction to R Workshop hosted by PwC, Midrand.\n Bianca Peterson with participants at the Introduction to R workshop, Johannesburg\nThis event was attended by over 20 participants, mostly from local businesses and organizations. Although Bianca and Heather were there because of the satRday, most of the participants were new to R and only came to the workshop. This demonstrates the potential for conferences to facilitate outreach events that grow the community. Due to fantastic support of the crowd-funding campaign, Forwards was able to award a scholarship to Ofentse Phuti-Rice, a Computer Science MSc student from Botswana. The scholarship enabled her to attend this workshop, the Web Scraping with R pre-satRday workshop led by Megan Beckett and Andrew Collier, and the satRday itself.\nAfter the Introduction to R workshop, Heather joined fellow satRday keynote Colin Fay to speak at R-Ladies Johannesburg. Colin spoke on how to contribute to the R ecosystem - everything from sharing what you’re learning to writing a package - while Heather spoke about publishing and promoting your packages. This time the dozen or so attendees were R enthusiasts, most of whom would be at the satRday workshops and/or conference.\n The folks at R-Ladies Johannesburg\nThe satRday workshops were the following day. Heather led a workshop using the latest iteration of the Forwards package development slides, with Bianca assisting. The workshop was open to all, however funding from the R Consortium supported scholarships for four women to attend: Astrid Radermacher, a postdoc at the University of Cape Town; Lillian Pazvakawambwa, a lecturer at the University of Namibia; Fransina Amutenya, a statistician at Namibia Statistics Agency and Caroline Akoth, Advocacy and Operations Lead, Women in GIS, Kenya. The scholarship enabled the recipients to attend the satRday conference as well as the workshop.\n Heather Turner leading the R Package Development workshop, Johannesburg.\nThe satRday itself was attended by over 100 people, with many folk travelling from across South Africa and beyond to attend.\n Participants waiting for the programme to start at satRday Johannesburg.\nThere was a packed programme of 2 keynote talks, 13 regular talks and 8 lightning talks - there are links to slides and videos in the programme. Heather gave a talk on Diversity and Inclusion in the R Community (Video, Slides), focusing on outreach to underrepresented groups beyond white women and the path to becoming an R (core) developer. The conference was also a great opportunity for networking, particularly among people from different cities/countries.\n Emmanuel Ọlámíjùwọ́n, co-organizer of Eswatini UseR group, with Heather Turner, satRday Johannesburg.\n\n\nEswatini\nAfter the satRday, Heather travelled to Eswatini to give a two-day workshop at the University of Eswatini, hosted by the Eswatini UseR group. Participants were mostly students/staff at the university, but a few came from outside organizations such as the revenue authority and a local non-profit. The workshop covered data import, data wrangling, data visualisation and linear modelling, and the participants created an R markdown report based on a case study.\n Participants at Introduction To R workshop, Eswatini, including two of the user group organizers at the back by the windows, L: Garikayi Chemhaka, R: Nontsikelelo Shongwe\nThere was a lot of interest in more advanced topics, such as handling missing data, working with big data and machine learning. At the end of the workshop, Heather gave a talk on the R Community and Free Resources so that participants would know how to get support and materials for further learning.\n Mbongeni Dube, co-organizer of Eswatini UseR group, outside the workshop venue.\n\n\nGaborone\nDue to a flight cancellation (unrelated to COVID-19), Heather was not able to visit Gaborone as planned. However the organizers from the new Botswana R Users group, along with co-organizers from WiMLDS Gaborone and PyData Botswana helped facilitate an Introduction to R tutorial, with Heather teaching remotely over Zoom. The tutorial gave a basic orientation of R/RStudio, before focusing on visualization with base R and ggplot2 (slides here, we skipped data wrangling).\nThe participants took some great photos, including our banner image and the one of women attendees below.\n Women that attended the Introduction To R workshop, Botswana.\nAfter the workshop, the Botswana R User group was officially launched. Heather gave her talk on the R Community and Free Resources, while Edson Kambeu gave an overview of the vision for the R User Group. Attendees took turns to introduce themselves: there were a number of students and people working as statisticians or data scientists; most people currently used SPSS or Python, but were interested to learn R.\n\n\nElsewhere\nThose are all the events that have taken place so far. The original aim was also to run a tutorial and launch a R User Group in Namibia. This proved to be too difficult to arrange to coincide with Heather’s visit to the area, but useful connections were made and organizers at the University of Namibia have applied for a grant from The R Consortium to help launch a user group. There is also some funding left over from the crowdfunder, which we hope to use to support a tutor from South Africa to lead a tutorial in Windhoek, when circumstances allow it. We have also made connections to people interested in R (and QGIS) training in Lesotho and hope to follow that up if we can.\n\n\nSummary\nWe’d like to thank all our supporters that made these events possible, especially the individuals that contributed to the crowdfunder. It was great that we were able to cover all the anticipated costs as well as fund some scholarships to the Johannesburg satRday and pre-conference workshops. The events helped to get many people started with R and hopefully inspired them to continue with it, supported by the local groups and wider community.\n\n\nPhoto credits\nPhotos from Gaborone by meetup attendees.\nPhoto of R-Ladies Johannesburg by Kirsty Lee Garson.\nPhoto of Eswatini UseR group by Emmanual Ọlámíjùwọ́n.\n\n\n\n\n\n\nReusehttps://creativecommons.org/licenses/by-sa/4.0/" }, { - "objectID": "docs/nonresponse_useR2016_survey/index.html", - "href": "docs/nonresponse_useR2016_survey/index.html", - "title": "Non-response in useR! 2016 Survey", + "objectID": "community.html", + "href": "community.html", + "title": "Community", "section": "", - "text": "The useR! survey received a total of 455 responses out of 904 attendees. Anticipating a high proportion of non-response, questions were included in the survey on participants’ gender, registration type and country of residence, with a view to adjusting observed counts in each cross-classified group to match the proportions in the total useR! 2016 population. Unfortunately the country of residence was not recorded during registration and could not be reliably derived from available information such as affiliation. Although registration type should have been available, in practice it was missing for about one third of participants. This leaves gender, which was (self-)recorded for presenters, but not for other attendees. In order to obtain a gender assignment for all participants, the first names were analysed with the genderizer package, which predicts gender from first name, based on profiles scraped from the web. For participants where the gender was unknown, the genderizer prediction was used if it was based on a sample > 10 and had probability > 0.9, otherwise the gender was assigned based on a manual web search, where this led to a clear assignment. This gave estimates of 235 female, 593 male and 76 undetermined.\nAssuming that the gender distribution is similar in the undetermined group, the survey population overrepresents female attendees by about 10%:\n\n\n\nGender\nSurvey Percentage\nAttendee Percentage\n\n\n\n\nFemale\n37.31\n28.38\n\n\nMale\n62.47\n71.62\n\n\nNon-Binary\n0.22\nNA\n\n\n\n(The assumption that the undetermined have a similar gender distribution seems reasonable, as similar estimates of attendee breakdown were obtained based on genderizer results only, where there were 52.17% undetermined). This over-representation of females is a common phenomenon in surveys and particularly unsurprising here as females may be more motivated to respond to a survey run by the Women in R taskforce." + "text": "Forwards partners with community groups within and beyond the R community to work towards more inclusive tech and open source/research software communities.\nThe R community groups with a particular mission to support members of underrepresented groups include:\n\nR-Ladies: the mission of R-Ladies is to achieve proportionate representation by encouraging, inspiring, and empowering people of genders currently underrepresented in the R community.\nAfricaR: working to achieve improved representation by encouraging, inspiring, and empowering the African population of all genders who are underrepresented in the global R community.\nMiR: MiR Community hopes to provide a space of belonging and support for people who identify as underrepresented minority R useRs. They aim to provide opportunities for underrepresented minority useRs to contribute to the R community.\nBlind R User Group: a mailing list for anyone interested in knowing more about (or improving) the use of R by blind people. This would include blind students, their support staff, or anyone having an interest in how blind people will make use of R and related tools.\nRainbow R (R LGBTQ+): a community that supports, promotes and connects LGBTQ+ people who code in the R language.\n\nIn addition, there are many general R User Groups open to all, some of which are listed in the following places:\n\nR Community Explorer a dashboard that tracks meetups listed on Meetup.com.\nR User Group List maintained on GitHub by the R consultancy Jumping Rivers. Others may be found by searching on Meetup or Facebook.\n\nForwards is a taskforce set up by the R Foundation, the not-for-profit organization that supports the R project. Other organizations we work with include:\n\nR Consortium a not-for-profit consortium of business set up to support the worldwide community of users, maintainers and developers of R software.\n\nThe R Consortium has a Diversity & Inclusion Working Group.\n\nWhy R? Foundation a non-governmental organization set up by a team of R enthusiasts coming from both business and academia who aim to support local R communities around the world." }, { - "objectID": "docs/nonresponse_useR2016_survey/index.html#background", - "href": "docs/nonresponse_useR2016_survey/index.html#background", - "title": "Non-response in useR! 2016 Survey", + "objectID": "contribution.html", + "href": "contribution.html", + "title": "Contribution", "section": "", - "text": "The useR! survey received a total of 455 responses out of 904 attendees. Anticipating a high proportion of non-response, questions were included in the survey on participants’ gender, registration type and country of residence, with a view to adjusting observed counts in each cross-classified group to match the proportions in the total useR! 2016 population. Unfortunately the country of residence was not recorded during registration and could not be reliably derived from available information such as affiliation. Although registration type should have been available, in practice it was missing for about one third of participants. This leaves gender, which was (self-)recorded for presenters, but not for other attendees. In order to obtain a gender assignment for all participants, the first names were analysed with the genderizer package, which predicts gender from first name, based on profiles scraped from the web. For participants where the gender was unknown, the genderizer prediction was used if it was based on a sample > 10 and had probability > 0.9, otherwise the gender was assigned based on a manual web search, where this led to a clear assignment. This gave estimates of 235 female, 593 male and 76 undetermined.\nAssuming that the gender distribution is similar in the undetermined group, the survey population overrepresents female attendees by about 10%:\n\n\n\nGender\nSurvey Percentage\nAttendee Percentage\n\n\n\n\nFemale\n37.31\n28.38\n\n\nMale\n62.47\n71.62\n\n\nNon-Binary\n0.22\nNA\n\n\n\n(The assumption that the undetermined have a similar gender distribution seems reasonable, as similar estimates of attendee breakdown were obtained based on genderizer results only, where there were 52.17% undetermined). This over-representation of females is a common phenomenon in surveys and particularly unsurprising here as females may be more motivated to respond to a survey run by the Women in R taskforce." + "text": "The Forwards on-ramps team work on initiatives to support useRs to become developeRs, with a focus on contributing to the R project via packages on CRAN/Bioconductor or via contribution to R Core. Find out more about specific projects below.\n\nFirst Contributions using GitHub/RStudio: Many R packages are version controlled using git and hosted on a platform such as GitHub or GitLab. This enables people from the general R community to submit contributions to packages to fix issues, e.g. to correct a typo in the documentation, to fix a bug or even to propose an improvement or new feature. The first-contributions repository is designed to give first-timers a place to practice the workflow of forking a GitHub repository, making a small change and submitting a pull request back to the original repository for the maintainers to review.\nR Contribution Working Group: This group is a collaboration between R Core, R community groups (including Forwards, the R Consortium Diversity and Inclusion Working Group, R-Ladies, MiR) and members of the wider R community. Its aim is to encourage new contributors to R core, with a focus on diversity and inclusion. See the R Contribution Working Group subsite for more information, including how to join the Slack group for anyone interested in R core contribution.\n\nSee also the Education page, which includes learning resources for useRs wanting to learn about package development." }, { - "objectID": "docs/nonresponse_useR2016_survey/index.html#adjusting-for-non-response", - "href": "docs/nonresponse_useR2016_survey/index.html#adjusting-for-non-response", - "title": "Non-response in useR! 2016 Survey", - "section": "Adjusting for non-response", - "text": "Adjusting for non-response\nIn order to adjust for the difference in gender balance between the sample and the full population, weights may be computed for males and females so that the ratio of females to males based on adjusted counts (sum of weights in each category) is equal to that estimated for the full sample. Specifically, the weight for females is 0.76 and the weight for males is 1.14.\nThese weights can then be used in further analysis, for example when tabulating by another survey variable. Here we will consider a few examples for illustration.\n\nAge\nThe unweighted and weighted densities have a very similar shape, but using the weighting shifts the density slightly to the left, i.e. when females are down-weighted there is a slight shift to a generally older population.\n\n\n\nEducation level\nHere there is very little difference between the unweighted and weighted counts.\n\n\n\nQ7\nCount\nAdj.Count\n\n\n\n\nProfessional degree or certification\n10\n10.67\n\n\nDoctorate\n199\n200.69\n\n\nMasters degree\n187\n186.06\n\n\nUndergraduate degree\n52\n50.63\n\n\nHigh school/Secondary school or lower\n3\n3.05\n\n\nNA\n7\n6.90\n\n\n\n\n\nEmployment status\nAgain the differences between unweighted and weighted counts are small here, however there is a consistent shift from less financially secure positions (student, unemployed and employed non-permenantly in academia) to more financially secure positions (employed permenantly in academia, employed in industry). This tallies with the younger distribution of females noted above.\n\n\n\nQ8\nCount\nAdj.Count\n\n\n\n\nEmployed in industry\n183\n186.24\n\n\nEmployed permanently in academia\n76\n78.08\n\n\nEmployed non-permanently in academia\n59\n57.10\n\n\nEmployed in government/non-profit\n70\n69.54\n\n\nSelf-employed\n6\n6.48\n\n\nRetired\n2\n2.29\n\n\nStudent\n44\n40.71\n\n\nUnemployed\n4\n3.42\n\n\nNA\n14\n14.14\n\n\n\n\n\nTime using R\nWith the weighted counts we see a slight shift towards greater experience; this again tallies with females being generally younger and less advanced in their careers.\n\n\n\nQ11\nCount\nAdj.Count\n\n\n\n\n> 10 years\n119\n123.28\n\n\n5-10 years\n132\n132.38\n\n\n2-5 years\n118\n118.05\n\n\n1-2 years\n35\n31.57\n\n\n6-12 months\n29\n28.17\n\n\n< 6 months\n9\n8.76\n\n\nNA\n16\n15.80\n\n\n\n\n\nRecreational use of R\nWith the weighted counts we see a shift towards using R for recreational activity alone or as well as for work. Since the weighting down-weights females relative to males this suggests males are more able or more willing to use R for fun.\n\n\n\n\n\n\n\n\nQ14\nCount\nAdj.Count\n\n\n\n\nFor both recreational and job/educational purposes.\n160\n169.41\n\n\nPrimarily as a recreational activity, in your free time;\n4\n4.58\n\n\nPrimarily as part of a job or educational course;\n275\n265.55\n\n\nNA\n19\n18.46\n\n\n\n\n\nSummary\nThe examples above illustrate that the difference between unweighted and weighted counts tends to be small and is unlikely to affect conclusions drawn about the distribution of a particular variable in the useR! population as a whole.\nWhere there is a material difference between unweighted and weighted counts, this can be attributed to gender, since the weighting only depends on this factor. In this case it would be more interesting to explore the gender difference by showing a summary grouped by gender and then the weighting becomes irrelevant as we are no longer trying to represent the whole population.\nSummarising by gender will necessarily exclude individuals that are non-binary or have not stated their gender. In addition, summarising by gender can result in (more) categories containing only a few individuals, which is undesirable as we wish to protect anonymity. Therefore a grouped summary should only be used when there is a substantive gender difference and small groups can be combined without too much loss of information. First considering the unweighted and weighted counts can help in making this judgement. Using the weights in this exploratory way is perhaps more appropriate than using them to adjust the counts, given that they are based in part on predicted data." + "objectID": "docs/MCA_community_useR2016_survey/index.html", + "href": "docs/MCA_community_useR2016_survey/index.html", + "title": "useR! 2016 participants and the R community: a multivariate analysis", + "section": "", + "text": "The useR! survey gathers responses to questions on different themes for 455 attendees: demographic characteristics, R programming and involvement in the R community. The separate analyses of each question in each theme are detailed in the posts Mapping useRs, useRs Relationship with R and Community Involvement of useRs. A multivariate analysis of the R programming questions is detailed in a companion report. Here, we perform MCA on the R community questions.\n\n\n\nQuestions are the following ones:\n\nQ18 Do you consider yourself part of the R community?\nQ19 Which of the following resources do you use for support? Select all that apply\n\nQ19_A The R mailing lists\nQ19_B The #rstats hashtag on Twitter\nQ19_C The R StackOverflow queues\nQ19_D The R IRC channel\nQ19_E The rOpenSci mailing lists or chat forums\nQ19_F The Bioconductor support site\nQ19_H Other\n\nQ20 What would be your preferred medium for R community news (e.g. events, webinars, opportunities)?\nQ21 Do you attend R user group meetings in your local area?\nQ22 If you do: you do: what type of user group is it?\nQ23 If you do not: why not?\nQ24 Which of the following would make you more likely to participate in the R community, or improve your experience? Tick any that apply.\n\nQ24_A New R user group near me (specify location in comments box)\nQ24_B New R user group near me aimed at my demographic (specify relevant group in comments box)\nQ24_C Free local introductory R workshops\nQ24_D Paid local advanced R workshops\nQ24_E R workshop at conference in my domain (specify domain/conference in comments box)\nQ24_F R workshop aimed at my demographic (specify relevant group in comments box)\nQ24_G Mentoring (e.g. first CRAN submission/useR! abstract submission/GitHub contribution)\nQ24_H Training in non-English language (specify language in comments box)\nQ24_I Training that accommodates my disability (specify disability in comments box)\nQ24_J Online forum to discuss R-related issues\nQ24_K Online support group for my demographic (specify relevant group in comments box)\nQ24_L Special facilities at R conferences (give further detail in comments box)\nQ24_M Comments on answers above\n\nQ25 What other ideas do you have for improving the R community?\nQ26 Do you have any feedback for the survey authors?\n\n\n\n\n\nQuestion Q20 has a category “others” which corresponds to free text answers. We add new categories for this variable by grouping common answers and we name the new variables with the suffix “_new’’. For instance, there is a variable Q20_new with a new category medium_R-bloggers.\nQuestion Q19_H also corresponds to free text answers. It has been recoded with Q19_H_new to Q19_N_new by grouping common answers: for instance, Q19_K_new has two categories Github_yes or Github_no.\nQ21, Q22 and Q23 have been merged in a variable Q21_new since Q22 and Q23 are filled-in depending on the answer on Q21. For example, for Q21 Do you attend R user group meetings in your local area?, if the respondent answers no, they answer Q23 If you do not: why not?, with I am too busy. This is coded in the variable Q21_new, with the category meeting_no_I am too busy.\nQ24_M, Q25 and Q26 are not analysed.\nNon-respondents identified in the MCA Rprogramming document are also excluded since they do not answer to R community questions as well.\nCategories are renamed to be easily understandable. In particular, the two categories for answers completed by checking a box are recoded as yes, if the box is checked, or recoded as no otherwise." }, { - "objectID": "docs/nonresponse_useR2016_survey/index.html#grouped-summaries", - "href": "docs/nonresponse_useR2016_survey/index.html#grouped-summaries", - "title": "Non-response in useR! 2016 Survey", - "section": "Grouped Summaries", - "text": "Grouped Summaries\nHere we show how the conclusions of the previous section might be applied to our illustrative questions.\n\nAge\nThe difference in density between weighted and unweighted is small but consistent across a wide age range so deserves further exploration. Since we are using a density summary there is no issue with small sub-groups.\nBreaking down by gender shows the difference in age distribution much more clearly:\n\n\n\nEducation level\nAlthough there is some evidence of a more educated male population (weighted counts shift to higher education levels) the difference is small. In addition the numbers without university-level education are very small and even combined with the missing group there is potential that individuals are identified when broken down by gender. Therefore it is best to keep genders combined here and base the final summary on unweighted counts.\n\n\n\nEmployment status\nHere the shift from unweighted counts to weighted counts is larger. Although there are small groups, these can reasonably be combined into an “Other” category.\n\n\n\nTime using R\nAgain there are material differences between unweighted and weighted counts, here the original groups can be left as is:\n\n\n\nRecreational use of R\nHere there is a clear difference between unweighted and weighted counts. As only four people (men) said that they used R primarily as a recreational activity, this can be combined with the missing category:" + "objectID": "docs/MCA_community_useR2016_survey/index.html#introduction", + "href": "docs/MCA_community_useR2016_survey/index.html#introduction", + "title": "useR! 2016 participants and the R community: a multivariate analysis", + "section": "", + "text": "The useR! survey gathers responses to questions on different themes for 455 attendees: demographic characteristics, R programming and involvement in the R community. The separate analyses of each question in each theme are detailed in the posts Mapping useRs, useRs Relationship with R and Community Involvement of useRs. A multivariate analysis of the R programming questions is detailed in a companion report. Here, we perform MCA on the R community questions.\n\n\n\nQuestions are the following ones:\n\nQ18 Do you consider yourself part of the R community?\nQ19 Which of the following resources do you use for support? Select all that apply\n\nQ19_A The R mailing lists\nQ19_B The #rstats hashtag on Twitter\nQ19_C The R StackOverflow queues\nQ19_D The R IRC channel\nQ19_E The rOpenSci mailing lists or chat forums\nQ19_F The Bioconductor support site\nQ19_H Other\n\nQ20 What would be your preferred medium for R community news (e.g. events, webinars, opportunities)?\nQ21 Do you attend R user group meetings in your local area?\nQ22 If you do: you do: what type of user group is it?\nQ23 If you do not: why not?\nQ24 Which of the following would make you more likely to participate in the R community, or improve your experience? Tick any that apply.\n\nQ24_A New R user group near me (specify location in comments box)\nQ24_B New R user group near me aimed at my demographic (specify relevant group in comments box)\nQ24_C Free local introductory R workshops\nQ24_D Paid local advanced R workshops\nQ24_E R workshop at conference in my domain (specify domain/conference in comments box)\nQ24_F R workshop aimed at my demographic (specify relevant group in comments box)\nQ24_G Mentoring (e.g. first CRAN submission/useR! abstract submission/GitHub contribution)\nQ24_H Training in non-English language (specify language in comments box)\nQ24_I Training that accommodates my disability (specify disability in comments box)\nQ24_J Online forum to discuss R-related issues\nQ24_K Online support group for my demographic (specify relevant group in comments box)\nQ24_L Special facilities at R conferences (give further detail in comments box)\nQ24_M Comments on answers above\n\nQ25 What other ideas do you have for improving the R community?\nQ26 Do you have any feedback for the survey authors?\n\n\n\n\n\nQuestion Q20 has a category “others” which corresponds to free text answers. We add new categories for this variable by grouping common answers and we name the new variables with the suffix “_new’’. For instance, there is a variable Q20_new with a new category medium_R-bloggers.\nQuestion Q19_H also corresponds to free text answers. It has been recoded with Q19_H_new to Q19_N_new by grouping common answers: for instance, Q19_K_new has two categories Github_yes or Github_no.\nQ21, Q22 and Q23 have been merged in a variable Q21_new since Q22 and Q23 are filled-in depending on the answer on Q21. For example, for Q21 Do you attend R user group meetings in your local area?, if the respondent answers no, they answer Q23 If you do not: why not?, with I am too busy. This is coded in the variable Q21_new, with the category meeting_no_I am too busy.\nQ24_M, Q25 and Q26 are not analysed.\nNon-respondents identified in the MCA Rprogramming document are also excluded since they do not answer to R community questions as well.\nCategories are renamed to be easily understandable. In particular, the two categories for answers completed by checking a box are recoded as yes, if the box is checked, or recoded as no otherwise." }, { - "objectID": "docs/nonresponse_useR2016_survey/index.html#conclusions", - "href": "docs/nonresponse_useR2016_survey/index.html#conclusions", - "title": "Non-response in useR! 2016 Survey", - "section": "Conclusions", - "text": "Conclusions\nWhere there is no material difference between genders, the over-representation of women in the sample is unimportant. Where there is a substantive difference, it is interesting to explore this difference in a grouped summary, where again the over-representation of women becomes irrelevant as males and females are summarised separately.\nTherefore rather than base final summaries on weighted counts, which are based in part on predicted data, it is better to use the weighted counts as a guide to when a grouped summary is appropriate." + "objectID": "docs/MCA_community_useR2016_survey/index.html#analysis", + "href": "docs/MCA_community_useR2016_survey/index.html#analysis", + "title": "useR! 2016 participants and the R community: a multivariate analysis", + "section": "Analysis", + "text": "Analysis\nMCA summarizes the relationships between the categories of the R community variables.\n\nTo interpret the main dimensions of variability in the response profiles, we study the proximities between categories. Indeed, two categories are close on the graph if most respondents taking the first category also take the other category.\n\nFirst dimension of variability\nThe first dimension (horizontal axis) opposes people that didn’t answer questions about involvement in the R community on the left, to the others on the right. More precisely, they did not answer Q21, Q18 and Q20 and did not check any boxes for the other questions (_no). Individuals with the smallest coordinates on the first dimension work more in the industry; this is confirmed by a statistical test, but this remains difficult to interpret.\n\n\nSecond dimension of variability\nOn the top, there are respondents who do not attend an R user group because they feel too inexperienced. They think that they would be more likely to participate in the R community or to improve their experience, if a user group, a workshop, or an online support dedicated to their socio-demographic group would be available. Facebook would be their preferred medium for R community news. They do not use Twitter (question Q19_B), (the category R_twitter_no corresponds to the answer The #rstats hashtag on Twitter for the question Which of the following resources do you use for support?). In addition, they do not like to use it as a medium for R community news (question Q20). They consider themselves as outside the R community.\nOn the bottom, in contrast, there are individuals who tend to consider themselves as part of the R community. They attend general R user group meetings and they use Twitter. Twitter would be their preferred medium for R community news.\n\n\n\nRelationship with demographic\nIn the following graph, answers about the demographic questions are projected as supplementary variables on the two first dimensions of variability. Supplementary variables are not used to build the dimensions of variability, but they are projected a posteriori to highlight relationships between the dimensions of variability and demographics. Thus, supplementary variables can be used to characterize the response profiles described previously.\nOnly demographic characteristics that are significantly related the R community profiles are represented. An analysis of variance with demographic variables as covariates, and the coordinates of the individuals on the dimensions as explanatory variables, has been performed.\n\nIt appears that people having an undergraduate degree or a master degree are located at the top of the graph, while those with a doctorate are at the bottom. This would imply that people with undergraduate degree or master degree are more likely to consider themselves as outside the R community than people having a doctorate. The same comment holds for women versus men. It is interesting to note, caregivers for children or adult dependents tend to be at the bottom of the graph, while non-caregivers are on the top.\nWe represent the age categories on the map since some confounding effects with other demographic variables could explain the previous results. Youngest people tend to be on the top of the second axis, which suggests that they consider themselves as outside the community.\n\nTo get more insights into this possible confounder effect, we created a new variable sex-age and represent it:\n\nIt highlights that both young (men and women) and women do not consider themselves as part of the R community.\n\n\nSimilarities between respondents\nA clustering of the participants is performed from their answers to questions about their involvement in the R community. More precisely a hierarchical clustering is performed on the principal components of MCA. The rationale is to improve the stability of the clustering by building it from denoised data rather than from the original dataset1. Several rules can be used to select the number of components used for the clustering. Here we choose 44 dimensions which corresponds to 95% of the projected inertia (variance) of the data.\nThe number of clusters is chosen according to the barplot of the inertia gains which suggests a partition with 3 clusters. However, this clustering is not relevant since most of respondents are in the same group:\n\n\n\n\n1\n2\n3\n\n\n\n\nsize\n12\n425\n6\n\n\n\nWe investigate the number of respondents in each group according to the number of components used to build the clustering:\n\n\n\n\nclust1\nclust2\nclust3\nclust4\nclust5\nclust6\nclust7\n\n\n\n\nncp=2\n12\n307\n124\n0\n0\n0\n0\n\n\nncp=3\n12\n208\n162\n61\n0\n0\n0\n\n\nncp=4\n12\n231\n139\n61\n0\n0\n0\n\n\nncp=5\n12\n212\n148\n65\n6\n0\n0\n\n\nncp=6\n12\n249\n160\n22\n0\n0\n0\n\n\nncp=7\n12\n269\n159\n3\n0\n0\n0\n\n\nncp=8\n12\n255\n173\n3\n0\n0\n0\n\n\nncp=9\n12\n236\n192\n3\n0\n0\n0\n\n\nncp=10\n12\n271\n157\n3\n0\n0\n0\n\n\nncp=11\n12\n273\n155\n3\n0\n0\n0\n\n\nncp=12\n12\n428\n3\n0\n0\n0\n0\n\n\nncp=13\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=14\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=15\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=16\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=17\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=18\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=19\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=20\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=21\n12\n425\n6\n0\n0\n0\n0\n\n\nncp=22\n12\n425\n6\n0\n0\n0\n0\n\n\n\nWe choose to keep 10 components as this will keep enough information, while highlighting a new cluster in the previous big one.\n\nRespondents are grouped in the clusters as follows:\n\n\n\n\n1\n2\n3\n4\n\n\n\n\n%\n2.71\n61.17\n35.44\n0.68\n\n\n\n\nFrom the previous interpretation of the two first dimensions of variability, the location of clusters on the graph allows providing a brief summary of the clusters: cluster 1 is the group of non-respondents, while cluster 2 contains some respondents who feel they are part of the R community unlike the cluster 3 respondents.\n\nCluster 1\nTo describe the first cluster more precisely, we use statistical tests to compare the proportion of each category in the cluster against the proportion in the population of the respondents.\nUnsurprisingly, there is an over-representation of people that didn’t answer the questions about the involvement in the R community. Using the demographic characteristics, we can see that they are mainly from the industry.\n\n\nCluster 2\nThe following categories are over-represented in cluster 2:\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ24=new_gp_near_no\n78.19\n92.62\n72.46\n< 2e-16\n\n\nQ18=in_Rcommunity_yes\n70.64\n94.10\n81.49\n< 2e-16\n\n\nQ21=Yes\n85.89\n51.66\n36.79\n< 2e-16\n\n\nQ21_new=meeting_yes_A general user group\n86.82\n41.33\n29.12\n1.1e-13\n\n\nQ19_B=R_twitter_yes\n85.59\n37.27\n26.64\n3.4e-11\n\n\nQ24_C=free_workshop_no\n66.75\n94.10\n86.23\n3.1e-09\n\n\nQ20_new=medium_Twitter\n90.00\n23.25\n15.80\n8.3e-09\n\n\nQ19=R_mailing_yes\n73.89\n49.08\n40.63\n4.8e-06\n\n\nQ24_B=new_gp_demo_no\n64.08\n97.42\n93.00\n7.9e-06\n\n\nQ21_new=meeting_no_It is not necessary (I have the support I need)\n96.15\n9.23\n5.87\n3.5e-05\n\n\nQ24_D=paid_workshop_no\n64.92\n91.51\n86.23\n7.5e-05\n\n\nQ19_C=R_StackOverflow_yes\n66.17\n81.55\n75.40\n0.00020\n\n\nQ21_new=meeting_no_I am too busy\n77.92\n22.14\n17.38\n0.00071\n\n\nQ7=Doctorate\n68.91\n49.08\n43.57\n0.00334\n\n\nQ1_new=Q1_new_Academic/Govt\n69.02\n46.86\n41.53\n0.00428\n\n\nQ24_F=demo_workshop_no\n62.65\n97.79\n95.49\n0.00481\n\n\nQ9=Part-time\n93.33\n5.17\n3.39\n0.00648\n\n\nQ7=Professional degree or certification\n100.00\n3.69\n2.26\n0.00687\n\n\nQ19_L_new=web_no\n62.50\n97.79\n95.71\n0.00928\n\n\nQ24_K=online_demo_no\n62.35\n97.79\n95.94\n0.01753\n\n\nQ19_F=Biocond_yes\n80.65\n9.23\n7.00\n0.01900\n\n\nQ2Q3=>58_Men\n85.00\n6.27\n4.51\n0.02259\n\n\nQ3_cat=>58\n81.48\n8.12\n6.09\n0.02320\n\n\nQ2=Men\n65.22\n66.42\n62.30\n0.02582\n\n\nQ2Q3=29-33_Men\n74.14\n15.87\n13.09\n0.02851\n\n\n\nThe numbers read as follows, e.g. for Q18: 70.64% of individuals who consider themselves as part of the R community are in cluster 2; in cluster 2 94.1% of the individuals consider themselves as part of the R community, and 81.49% in the population of all the respondents consider themselves as part of the R community. The test is significant which implies that this cluster can be considered as a cluster with an over-representation of people considering themselves as part of the community. We conclude they are not interested in free workshops, online demos, etc. According to the demographic characteristics, there is an over-representation of people employed permanently in academia, people with caring responsibilities, as well as a significantly larger proportion of men and people with a doctorate.\nWe studied the categories under-represented in the cluster. However, since most of variables are binary, we do not get new information from this table. We note however that young people are under-represented, as well as people who didn’t participate in R user group meetings because of inexperience.\n\n\nCluster 3\n\n\n\n\n\n\n\n\n\n\n\nCla/Mod\nMod/Cla\nGlobal\np.value\n\n\n\n\nQ24=new_gp_near_yes\n81.97\n63.69\n27.54\n< 2e-16\n\n\nQ21_new=meeting_no_There is no group nearby/the group is inactive\n78.82\n42.68\n19.19\n< 2e-16\n\n\nQ21=No\n50.75\n86.62\n60.50\n< 2e-16\n\n\nQ18=in_Rcommunity_no\n76.81\n33.76\n15.58\n2.4e-14\n\n\nQ24_C=free_workshop_yes\n73.77\n28.66\n13.77\n5.9e-11\n\n\nQ21_new=meeting_no_I feel too inexperienced\n90.32\n17.83\n7.00\n7.2e-11\n\n\nQ19_B=R_twitter_no\n43.69\n90.45\n73.36\n2.5e-10\n\n\nQ24_D=paid_workshop_yes\n62.30\n24.20\n13.77\n4.8e-06\n\n\nQ24_B=new_gp_demo_yes\n74.19\n14.65\n7.00\n6.9e-06\n\n\nQ20_new=medium_Website\n52.73\n36.94\n24.83\n1.8e-05\n\n\nQ19=R_mailing_no\n42.97\n71.97\n59.37\n5.6e-05\n\n\nQ19_L_new=web_yes\n68.42\n8.28\n4.29\n0.00351\n\n\nQ20_new=medium_Facebook\n66.67\n8.92\n4.74\n0.00351\n\n\nQ8=Q8_Employed in industry\n42.37\n47.77\n39.95\n0.01354\n\n\nQ3_cat=20-28\n45.83\n28.03\n21.67\n0.01803\n\n\nQ24_F=demo_workshop_yes\n60.00\n7.64\n4.51\n0.02503\n\n\nQ7=Undergraduate degree\n50.00\n15.92\n11.29\n0.02609\n\n\nQ24_K=online_demo_yes\n61.11\n7.01\n4.06\n0.02707\n\n\nQ2Q3=20-28_Women\n50.00\n15.29\n10.84\n0.02974\n\n\nQ20_new=medium_Google+\n100.00\n1.91\n0.68\n0.04396\n\n\nQ7=High school/Secondary school or lower\n100.00\n1.91\n0.68\n0.04396\n\n\n\nIn this cluster, there is an over-representation of those who adhere to most of the proposals to increase their participation in the R community. Most of them have never participated in a user group meeting. The cluster gathers a large number of people who use blogs to get help, but also a large proportion of people who do not use Twitter. They prefer to use a medium like Facebook or mailing lists for news.\nFrom a demographic point of view, the cluster contains a significantly higher proportion of women than the respondent population, and a larger proportion of those with a master’s or undergraduate degree. People under the age of 30 are also over-represented.\nNote that we need to be cautious concerning the interpretation of the clustering as it varies depending on the number of MCA components selected. The stability of the solution should be investigated further. In addition, the number of individuals per cluster may slightly vary as there is a “consolidation step”2 which is applied, i.e. a k-means algorithm applied after the hierarchical clustering." }, { - "objectID": "edu/brisbane.html", - "href": "edu/brisbane.html", - "title": "Forwards", + "objectID": "docs/MCA_community_useR2016_survey/index.html#footnotes", + "href": "docs/MCA_community_useR2016_survey/index.html#footnotes", + "title": "useR! 2016 participants and the R community: a multivariate analysis", + "section": "Footnotes", + "text": "Footnotes\n\n\nFor more details about the classification based on principal components methods, see: Francois Husson, Jerome Pages, Sebastien Le. Exploratory Multivariate Analysis by Example Using R. CRC Press Taylor & Francis, pp.240, 2010, Chapman & Hall/CRC Computer Science & Data Analysis.↩︎\nFor more details about the classification based on principal components methods, see: Francois Husson, Jerome Pages, Sebastien Le. Exploratory Multivariate Analysis by Example Using R. CRC Press Taylor & Francis, pp.240, 2010, Chapman & Hall/CRC Computer Science & Data Analysis.↩︎" + }, + { + "objectID": "docs/index.html", + "href": "docs/index.html", + "title": "Reports", "section": "", - "text": "R Foundation taskforce on women and other under-represented groups\n\n\n\nRiver City Labs\n\n\n\n\n\nThis workshop is open to high school girls in year 11 who are interested in STEM, coding, and data analysis. No prior coding experience required.\nAPPLY NOW!\n\n\n\nHave you ever wondered how data scientists formulate questions, analyze and visualize data, and draw conclusions? In this workshop for Brisbane high school girls interested in STEM, coding, and data analysis, students will be introduced to coding in R through an investigation of Atlas of Living Australia data, looking at what wildlife lives around Brisbane. Participants will receive a certificate of completion at the end of the workshop.\n\n\n\n\n Data source: OECD PISA\n\n\n Brush turkeys in Brisbane\n\n\n Data source: ALA\n\n\n\n\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Students are responsible for their own transportation to and from the workshop. Morning, afternoon tea and lunch will be provided.\n\n\n\nDi Cook: Di Cook is a professor of business analytics at Monash University. She has a B.Sc/Di.Ed in Mathematics and Statistics from University of New England, and MSc/PhD in Statistics from Rutgers University in the USA. Prior to joining Monash in 2015, she spent 20 years teaching data science at Iowa State University. Di is a member of the R foRwards taskforce, a member of the R Foundation, elected Fellow of the American Statistical Association, past editor for the Journal of Computational and Graphical Statistics, and current chair of the American Statistical Association section on Statistical Graphics.\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email rowforwards@gmail.com with any questions, and see here for more information about this workshop series.\nAPPLY NOW!\nWorkshop flyer PDF" + "text": "2017-06-18: useR! 2016 participants and the R community: a multivariate analysis\n2017-06-17: useR! 2016 participants and R programming: a multivariate analysis\n2016-10-07: Non-response in useR! 2016 Survey\n\n\n\n2016-04-09: Recommendations to increase the Participation of Women at useR! Conferences" }, { - "objectID": "edu/brisbane.html#acems-and-forwards-r-coding-workshop-for-high-school-girls", - "href": "edu/brisbane.html#acems-and-forwards-r-coding-workshop-for-high-school-girls", - "title": "Forwards", + "objectID": "docs/index.html#survey-reports", + "href": "docs/index.html#survey-reports", + "title": "Reports", "section": "", - "text": "R Foundation taskforce on women and other under-represented groups\n\n\n\nRiver City Labs\n\n\n\n\n\nThis workshop is open to high school girls in year 11 who are interested in STEM, coding, and data analysis. No prior coding experience required.\nAPPLY NOW!\n\n\n\nHave you ever wondered how data scientists formulate questions, analyze and visualize data, and draw conclusions? In this workshop for Brisbane high school girls interested in STEM, coding, and data analysis, students will be introduced to coding in R through an investigation of Atlas of Living Australia data, looking at what wildlife lives around Brisbane. Participants will receive a certificate of completion at the end of the workshop.\n\n\n\n\n Data source: OECD PISA\n\n\n Brush turkeys in Brisbane\n\n\n Data source: ALA\n\n\n\n\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Students are responsible for their own transportation to and from the workshop. Morning, afternoon tea and lunch will be provided.\n\n\n\nDi Cook: Di Cook is a professor of business analytics at Monash University. She has a B.Sc/Di.Ed in Mathematics and Statistics from University of New England, and MSc/PhD in Statistics from Rutgers University in the USA. Prior to joining Monash in 2015, she spent 20 years teaching data science at Iowa State University. Di is a member of the R foRwards taskforce, a member of the R Foundation, elected Fellow of the American Statistical Association, past editor for the Journal of Computational and Graphical Statistics, and current chair of the American Statistical Association section on Statistical Graphics.\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email rowforwards@gmail.com with any questions, and see here for more information about this workshop series.\nAPPLY NOW!\nWorkshop flyer PDF" + "text": "2017-06-18: useR! 2016 participants and the R community: a multivariate analysis\n2017-06-17: useR! 2016 participants and R programming: a multivariate analysis\n2016-10-07: Non-response in useR! 2016 Survey" }, { - "objectID": "edu/index.html", - "href": "edu/index.html", - "title": "Education", + "objectID": "docs/index.html#recommendations-to-the-r-foundation", + "href": "docs/index.html#recommendations-to-the-r-foundation", + "title": "Reports", "section": "", - "text": "The Forwards teaching team support the work of the taskforce via the following projects:" + "text": "2016-04-09: Recommendations to increase the Participation of Women at useR! Conferences" }, { - "objectID": "edu/index.html#education-blog-posts", - "href": "edu/index.html#education-blog-posts", - "title": "Education", - "section": "Education blog posts", - "text": "Education blog posts\n\n\n \n \n \n Order By\n Default\n \n Title\n \n \n Date - Oldest\n \n \n Date - Newest\n \n \n Author\n \n \n \n \n \n \n \n\n\n\n\n \n\n\n\n\nGirls Coding Workshop, Melbourne\n\n\n\n\n\nGirls Coding Workshop, Melbourne\n\n\n\n\n\n\nNov 20, 2017\n\n\nDi Cook\n\n\n\n\n\n\n \n\n\n\n\nHavanaR Workshop 2018\n\n\n\n\n\nAnnouncement of joint >eR-Biostat and Forwards workshop in Havana, on visualisation methods and exploratory analysis of high dimensional and multivariate datasets in R.\n\n\n\n\n\n\nJul 7, 2018\n\n\nZiv Shkedy, Julie Josse\n\n\n\n\n\n\n \n\n\n\n\nRecap of R-Ladies Charlottesville Forwards Workshop\n\n\n\n\n\nLessons from R-Ladies Charlottesville Forwards Workshop\n\n\n\n\n\n\nNov 22, 2019\n\n\nAngela Li, Samantha Toet\n\n\n\n\n\n\n \n\n\n\n\nSouthern Africa Project 2020\n\n\n\n\n\nReview of the R training and community events organized as part of the Forwards Southern Africa Project 2020, in South Africa, Eswatini and Botswana.\n\n\n\n\n\n\nMay 25, 2020\n\n\nHeather Turner\n\n\n\n\n\n\n \n\n\n\n\nWorkshops for Women and Girls\n\n\n\n\n\nRound up of Forwards workshops supported by a grant from the R Consortium, to develop R package development skills among women and R coding skills among high school girls.\n\n\n\n\n\n\nSep 22, 2019\n\n\nForwards Teaching Team\n\n\n\n\n\n\nNo matching items" + "objectID": "docs/recommendations_user/index.html", + "href": "docs/recommendations_user/index.html", + "title": "Recommendations to increase the Participation of Women at useR! Conferences", + "section": "", + "text": "The following recommendations are made for future useR! conferences, as achievable actions to promote the inclusion of women.\n\n\nSince 2014, 2/6 invited speakers have been women. Although a 50:50 gender split is something to strive for, we are aware that this would be a big jump and the focus should be on sustaining the current level in the medium term. The step up in 2014 has already helped to raise the profile of women in the R community.\n\n\n\nWe recommend that the program committee is selected to be approximately 50:50 men and women. Women have in fact been well-represented in the past, e.g. useR! 2015 had 4/11 women and useR! 2016 has 7/13 women. Being on the program committee is a boost to the women selected: recognising their expertise, providing experience for their CV, raising their profile in the R community and potentially reducing the cost of their attendance.\n\n\n\nSimilarly we recommend that 50% of the sessions are chaired by women, ideally with women making up 50% of the session chairs (often people chair multiple sessions). Since the program committee are often called upon to chair sessions, this should follow to some degree from the previous recommendation. However it is also an opportunity to increase the involvement of women on the edges of the R community, e.g. local women who have not previously had much involvement in useR!, regular attendees who have previously not had a formal role, women working in business/industry who are often not considered for such roles, etc.\n\n\n\nNot all useR! conferences have panel discussions, but with the exception of the heR panel (“Why aren’t more women R users?”) at useR! 2014, women have barely been represented. We recommend that any panels should reflect the composition of recent useR!s, i.e. at least 20% should be women.\n\n\n\nTo demonstrate the commitment of the R community to promoting the inclusion of women, we recommend publishing recent statistics of gender balance on the conference website. A good example is set here http://www.lorneproteins.org/policies/. We plan to collate such statistics on the Task Force webpage (https://forwards.github.io/), so that such tables could easily be produced for future useR!s." }, { - "objectID": "edu/workshops/index.html", - "href": "edu/workshops/index.html", - "title": "Workshops for Women and Girls", + "objectID": "docs/recommendations_user/index.html#recommendations", + "href": "docs/recommendations_user/index.html#recommendations", + "title": "Recommendations to increase the Participation of Women at useR! Conferences", "section": "", - "text": "Overview\nThanks to generous funding from the R Consortium, Forwards is pleased to offer the following workshops to support the development of coding skills and increase the participation of women in the R community:\n\nWorkshops for women are designed for women with some R coding experience who wish to learn more about package development, thereby addressing the skills gap that exists within the R community. As of 2016, an analysis of CRAN package maintainers estimated that fewer than 15% were women, and a useR! participant survey found that women were less likely than men to have experience contributing to or writing packages. Workshop participants learn to make code into an R package, do collaborative coding with GitHub, write a vignette or an article, build a package web page, and submit a package to CRAN. Participants can bring their own code that they wish to develop into a package or work with a Forwards example.\nWorkshops for high school girls serve as an introduction to coding in R and are designed for students interested in STEM, coding, and data analysis. Participants learn about plotting data, web scraping, and the development of Shiny apps. A selection of topics related to contemporary current affairs are used, and where possible, incorporate data specific to the workshop’s geographic location.\n\n\n\nUpcoming workshops\n\nPackage development workshop for women & other underrepresented groups at the University York\n2020-01-07, York, UK\nFree to attend, travel scholarships available for travel within the UK. More details.\nInstructors: Emma Rand, Susannah Cowtan\n\n\n\nPast Workshops\n\nForwards and ACEMS R Coding Workshop for Year 11 Girls at River City Labs\n2019-03-30, Brisbane, Australia\nFree to attend, More details\nInstructors: Di Cook and a team of brilliant young women\nDevelop Packages in R at UCD O’Brien Centre for Science\n2019-04-06, Dublin, Ireland\nThere is a small charge of EUR 5.85 to cover training materials, however tea/coffee and lunch are provided.\nBook your ticket\nInstructors: Isabella Gollini, assisted by Bruna Wundervald, Chiara Cotroneo, and Jo Niec.\nWomen’s Package Development Workshop jointed hosted with R-Ladies Chicago\n2019-02-23 Chicago, USA\nInstructor: Stephanie Kirmer and Angela Li\nData Science in R: Coding Workshop for 11th and 12th Grade Girls at AT&T NYC Data Science Research Center\n2018-10-27 New York City, USA\nInstructors: Emily Dodwell and Joyce Robbins\nUpgrade Your Workflow with a Custom Package at Cardiff satRday\n2018-06-23 Cardiff, Wales, United Kingdom\nInstructor: Heather Turner\nPackage Development Workshop for Women: Everything you need to know to create your own R package at R Ladies Melbourne by Earo Wang, slides, code 2018-05-24 Melbourne, Australia\nPackage Development Workshop for Women at eRum 2018\n2018-05-14 Budapest, Hungary\nInstructors: Heather Turner and Isabella Gollini\nCoding Workshop for 12th Grade Girls at The University of Auckland\n2017-12-08 Auckland, New Zealand\nInstructor: Di Cook\nWomen’s Coding Workshop at The University of Auckland\n2017-12-07 Auckland, New Zealand\nInstructors: Jenny Bryan, Di Cook, and Hadley Wickham\nCoding Workshop for 11th Grade Girls at Kathleen Syme Library\n2017-10-28 Melbourne, Australia\nInstructor: Di Cook\n\n\n\nCode of Conduct\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\nComputing Information\nIf possible, please install the most recent versions of the following software on your laptop prior to the workshop:\n\nR 3.5.1 “Feather Spray” (release date 2018-07-02)\nRStudio Desktop 1.1.456 (release date 2018-07-19)\n\nIf you have trouble, there will be technical support prior to the start of the workshop (arrive 30 minutes early).\n\n\nWorkshop Materials\nWorkshop materials are available on GitHub under a CC-BY-NC 3.0 license." + "text": "The following recommendations are made for future useR! conferences, as achievable actions to promote the inclusion of women.\n\n\nSince 2014, 2/6 invited speakers have been women. Although a 50:50 gender split is something to strive for, we are aware that this would be a big jump and the focus should be on sustaining the current level in the medium term. The step up in 2014 has already helped to raise the profile of women in the R community.\n\n\n\nWe recommend that the program committee is selected to be approximately 50:50 men and women. Women have in fact been well-represented in the past, e.g. useR! 2015 had 4/11 women and useR! 2016 has 7/13 women. Being on the program committee is a boost to the women selected: recognising their expertise, providing experience for their CV, raising their profile in the R community and potentially reducing the cost of their attendance.\n\n\n\nSimilarly we recommend that 50% of the sessions are chaired by women, ideally with women making up 50% of the session chairs (often people chair multiple sessions). Since the program committee are often called upon to chair sessions, this should follow to some degree from the previous recommendation. However it is also an opportunity to increase the involvement of women on the edges of the R community, e.g. local women who have not previously had much involvement in useR!, regular attendees who have previously not had a formal role, women working in business/industry who are often not considered for such roles, etc.\n\n\n\nNot all useR! conferences have panel discussions, but with the exception of the heR panel (“Why aren’t more women R users?”) at useR! 2014, women have barely been represented. We recommend that any panels should reflect the composition of recent useR!s, i.e. at least 20% should be women.\n\n\n\nTo demonstrate the commitment of the R community to promoting the inclusion of women, we recommend publishing recent statistics of gender balance on the conference website. A good example is set here http://www.lorneproteins.org/policies/. We plan to collate such statistics on the Task Force webpage (https://forwards.github.io/), so that such tables could easily be produced for future useR!s." }, { - "objectID": "index.html", - "href": "index.html", + "objectID": "docs/recommendations_user/index.html#other-issues-to-consider", + "href": "docs/recommendations_user/index.html#other-issues-to-consider", + "title": "Recommendations to increase the Participation of Women at useR! Conferences", + "section": "Other Issues to Consider", + "text": "Other Issues to Consider\nThe following sections outline some other issues that we recommend organisers of useR! consider to encourage the participation of women.\n\nTutorials\nWe have not evaluated the proportion of women tutors at useR! conferences over the years, but note that 6/18 tutorials are being presented by women at useR! 2016. This is in line with the proportion of invited speakers, so seems a reasonable proportion to aim for. This may be hard to put into practice as tutorials are generally contributed rather than invited, however gender balance might be taken into account when ranking submissions or making a final selection.\n\n\nQuotas\nA large proportion of abstracts contributed to useR! are accepted in some form and there is no evidence of gender bias in the rejections or the assigned presentation format. Quotas might be considered in particular cases to encourage the participation of women. Lightning talks may be particularly suitable for this as the number of abstracts is often much greater than the number of slots. The following links provide good arguments for using quotas: http://womeninscienceaust.org/2015/11/15/achieving-gender-balance-in-less-than-3-years/; http://curt-rice.com/2014/07/03/2-ways-quotas-for-women-raise-quality/. Scope for using quotas may be limited by the gender balance in submitted abstracts: 50:50 may simply not be possible. Alternative actions to encourage the contribution of women might still be considered, e.g. favouring women presenters when ranking borderline abstracts.\n\n\nOutreach to Women\nEfforts should be made to attract women to the conference. An example from useR! 2016 was to email prominent female R users inviting them to the conference and asking them to encourage their colleagues/students, particularly women, to participate. Another idea might be to provide a template email at the end of the registration form to invite a colleague or friend to useR!, with an encouragement to reach out to potential female participants.\n\n\nLocal Groups\nIf there are local coding groups for women, it is worth considering whether these groups can be involved in any way. There might be a student society for women in computer science or an R-ladies group, for example.\n\n\nScholarships/Funding\nFunding obviously plays a large part in the ability of women to attend useR!. useR! 2016 is offering scholarships aimed at young researchers (funded by the American Statistical Association) and diversity scholarships aimed at minority groups such as LGBT people or people with disabilities, as well as women. Links to any external funding sources might be added to the conference website.\n\n\nChildcare/Family-friendliness\nThe family-friendliness of the conference should also be considered:\n\nIs childcare available on campus/at any of the hotels? Such information would be useful to put on the website.\nCould any sponsorship money be allocated to assistance with childcare?\nIs there any potential for a “family room” suitable for participants to take children where (the main) talks could be streamed?\nAre children welcome in sessions?" + }, + { + "objectID": "docs/recommendations_user/index.html#reporting-back", + "href": "docs/recommendations_user/index.html#reporting-back", + "title": "Recommendations to increase the Participation of Women at useR! Conferences", + "section": "Reporting Back", + "text": "Reporting Back\nWe hope that following the recommendations and considering the issues above will help to increase the participation of women in useR! conferences. To assist with this endeavour, conference organisers should share the outcomes of any initiatives to increase diversity. In particular, the gender of participants should be recorded to monitor the gender balance of attendees, invited speakers, presenters of contributed presentations/tutorials (broken down by presentation format), session chairs, and members of the local and program committees." + }, + { + "objectID": "edu/chicago.html", + "href": "edu/chicago.html", "title": "Forwards", "section": "", - "text": "Leading the R community forwards in widening the participation of women and other under-represented groups.\nFind out more about the task force." + "text": "Materials for this workshop, including slides and sample code, can be found at this Github repository.\n\n\n\nCenter for Spatial Data Science\n5735 S Ellis Ave, 2nd Floor\nChicago, Illinois 60637\n\n\n\n\n\nApplications are available at this Google Form. We encourage you to apply, especially if you’ve never developed a package before. We’ll walk you through the basics, and you’ll leave having put together your first R package. Applications for out-of-town attendees will close on January 15, 2019, while applications for attendees based in Chicago will close on February 2, 2019.\nApply now!\n\n\n\nCurious about package development, but not sure where to start? This workshop is for you! Run by R-Ladies Chicago, the goal of this workshop is to empower you to start contributing back to the R ecosystem with package development. We’ll be using materials developed by Hadley Wickham, Jenny Bryan, and Di Cook for the Forwards teaching team.\nBy the end of this day-long workshop, you should know how to:\n\nmake your code into an R package,\ndo collaborative coding with GitHub,\nwrite a vignette or an article,\nbuild a web page for your package, and\nsubmit a package to CRAN.\n\nBring your own code that you want to make into a package, or work with our example.\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Breakfast and lunch will be provided.\nWe may be able to provided limited travel grants to out-of-town attendees, so please indicate on the application if you need support. Additionally, please let us know on the application if you will need childcare.\n\n\n\nStephanie Kirmer and Angela Li of R-Ladies Chicago co-taught the workshop. Stephanie is a Senior Data Scientist at Uptake and Angela is the R Spatial Advocate at the Center for Spatial Data Science.\nOur helpers were Katherine Simeon, Ola Giwa, and Nicole Burke from R-Ladies Chicago - thank you for your time!\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email angela [at] rladies.org with any questions, and see the main Education page for more information about Forwards teaching initiatives." }, { - "objectID": "index.html#mission", - "href": "index.html#mission", + "objectID": "edu/chicago.html#womens-package-development-workshop-by-r-ladies-chicago-and-forwards", + "href": "edu/chicago.html#womens-package-development-workshop-by-r-ladies-chicago-and-forwards", "title": "Forwards", "section": "", - "text": "Leading the R community forwards in widening the participation of women and other under-represented groups.\nFind out more about the task force." + "text": "Materials for this workshop, including slides and sample code, can be found at this Github repository.\n\n\n\nCenter for Spatial Data Science\n5735 S Ellis Ave, 2nd Floor\nChicago, Illinois 60637\n\n\n\n\n\nApplications are available at this Google Form. We encourage you to apply, especially if you’ve never developed a package before. We’ll walk you through the basics, and you’ll leave having put together your first R package. Applications for out-of-town attendees will close on January 15, 2019, while applications for attendees based in Chicago will close on February 2, 2019.\nApply now!\n\n\n\nCurious about package development, but not sure where to start? This workshop is for you! Run by R-Ladies Chicago, the goal of this workshop is to empower you to start contributing back to the R ecosystem with package development. We’ll be using materials developed by Hadley Wickham, Jenny Bryan, and Di Cook for the Forwards teaching team.\nBy the end of this day-long workshop, you should know how to:\n\nmake your code into an R package,\ndo collaborative coding with GitHub,\nwrite a vignette or an article,\nbuild a web page for your package, and\nsubmit a package to CRAN.\n\nBring your own code that you want to make into a package, or work with our example.\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Breakfast and lunch will be provided.\nWe may be able to provided limited travel grants to out-of-town attendees, so please indicate on the application if you need support. Additionally, please let us know on the application if you will need childcare.\n\n\n\nStephanie Kirmer and Angela Li of R-Ladies Chicago co-taught the workshop. Stephanie is a Senior Data Scientist at Uptake and Angela is the R Spatial Advocate at the Center for Spatial Data Science.\nOur helpers were Katherine Simeon, Ola Giwa, and Nicole Burke from R-Ladies Chicago - thank you for your time!\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email angela [at] rladies.org with any questions, and see the main Education page for more information about Forwards teaching initiatives." }, { - "objectID": "index.html#news", - "href": "index.html#news", + "objectID": "edu/nyc.html", + "href": "edu/nyc.html", "title": "Forwards", - "section": "News", - "text": "News\nFor more details on past workshops, see the Edu section.\n2019/05/25 First ever R conference in East Africa: SatRdays Kampala 2019 Lend your support to this pathbreaking conference by contributing to SatRdays Kampala’s Indiegogo campaign\n\n2019-04-06, Dublin Isabella Gollini, with Bruna Wundervald, Chiara Cotroneo, and Jo Niec, teach “Develop Packages in R”\n2019-03-30, Brisbane Di Cook and a team of brilliant women teach “R Coding Workshop for Year 11 Girls”\n2019-02-23, Chicago Stephanie Kirmer and Angela Li teach “Women’s Package Development Workshop”, jointed hosted with R-Ladies Chicago\n2018-10-27, New York City Emily Dodwell and Joyce Robbins lead “Data Science in R: Coding Workshop for 11th and 12th Grade Girls”\n2018-07-30, Vancouver Di Cook serves as panelist on late breaking session at JSM2018, Addressing Sexual Misconduct in the Statistics Community Organizer blog post\n2018-06-23, Cardiff, Wales Heather Turner teaches “Upgrade Your Workflow with a Custom Package” at Cardiff satRday\n2018-05-24, Melbourne Earo Wang leads “Package Development Workshop for Women: Everything you need to know to create your own R package” at R Ladies Melbourne slides, code\n2018-05-14, Budapest Package Development Workshop for Women at eRum 2018\nolder news items" + "section": "", + "text": "R Foundation taskforce on women and other under-represented groups\n\n\n\nAT&T NYC Data Science Research Center\n33 Thomas Street, 1st Floor\nNew York, NY 10007\n\n\n\n\n\nThis workshop is open to high school girls in grades 11 and 12 who are interested in STEM, coding, and data analysis. No prior coding experience required. Applicants will be notified of acceptance status by early/mid October.\nAPPLY NOW!\n\n\n\nHave you ever wondered how data scientists formulate questions, analyze and visualize data, and draw conclusions? In this workshop for NYC high school girls interested in STEM, coding, and data analysis, students will be introduced to coding in R through an investigation of NYC transportation data: Citibike, Taxi, and Flights. Participants will receive a certificate of completion at the end of the workshop.\n\n\n\nTransportation data is rich with potential insights into how people move around NYC.\n\n\n\n Source\n\n\n Source\n\n\n Source\n\n\n\n\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Students are responsible for their own transportation to and from the workshop, however each participant will be provided with a 2-trip MetroCard to reimburse the cost of travel. Lunch will be provided.\n\n\n\nEmily Dodwell: Emily Dodwell is a Senior Inventive Scientist in the Statistics Research Department at AT&T Labs and a member of the R Forwards teaching team. Prior to joining AT&T Labs in 2015, Emily taught high school math for three years at Choate Rosemary Hall. She received her M.A. in statistics from Yale University and B.A. in mathematics from Smith College.\nJoyce Robbins: Joyce Robbins, Ph.D., is Lecturer in Discipline in the Statistics Department at Columbia University, where she specializes in data visualization. She is a member of the R Forwards teaching team, and she was elected to serve as publications officer of the Statistical Graphics Section of the American Statistical Association Section beginning in 2018. Robbins received her doctorate in sociology from Columbia University, her M.A. in sociology and anthropology from Tel Aviv University and her B.S.E. in civil engineering and operations research from Princeton University.\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email rowforwards@gmail.com with any questions, and see here for more information about this workshop series.\nAPPLY NOW!\nWorkshop flyer PDF" }, { - "objectID": "index.html#mastodon-posts", - "href": "index.html#mastodon-posts", + "objectID": "edu/nyc.html#data-science-in-r-nyc-coding-workshop-for-high-school-girls-11th-and-12th-grades", + "href": "edu/nyc.html#data-science-in-r-nyc-coding-workshop-for-high-school-girls-11th-and-12th-grades", "title": "Forwards", - "section": "Mastodon posts", - "text": "Mastodon posts\n\n\n\n\n\n<div class=\"loading-spinner\"></div>" + "section": "", + "text": "R Foundation taskforce on women and other under-represented groups\n\n\n\nAT&T NYC Data Science Research Center\n33 Thomas Street, 1st Floor\nNew York, NY 10007\n\n\n\n\n\nThis workshop is open to high school girls in grades 11 and 12 who are interested in STEM, coding, and data analysis. No prior coding experience required. Applicants will be notified of acceptance status by early/mid October.\nAPPLY NOW!\n\n\n\nHave you ever wondered how data scientists formulate questions, analyze and visualize data, and draw conclusions? In this workshop for NYC high school girls interested in STEM, coding, and data analysis, students will be introduced to coding in R through an investigation of NYC transportation data: Citibike, Taxi, and Flights. Participants will receive a certificate of completion at the end of the workshop.\n\n\n\nTransportation data is rich with potential insights into how people move around NYC.\n\n\n\n Source\n\n\n Source\n\n\n Source\n\n\n\n\n\n\n\nThanks to funding from the R Consortium, this workshop is free for participants. Students are responsible for their own transportation to and from the workshop, however each participant will be provided with a 2-trip MetroCard to reimburse the cost of travel. Lunch will be provided.\n\n\n\nEmily Dodwell: Emily Dodwell is a Senior Inventive Scientist in the Statistics Research Department at AT&T Labs and a member of the R Forwards teaching team. Prior to joining AT&T Labs in 2015, Emily taught high school math for three years at Choate Rosemary Hall. She received her M.A. in statistics from Yale University and B.A. in mathematics from Smith College.\nJoyce Robbins: Joyce Robbins, Ph.D., is Lecturer in Discipline in the Statistics Department at Columbia University, where she specializes in data visualization. She is a member of the R Forwards teaching team, and she was elected to serve as publications officer of the Statistical Graphics Section of the American Statistical Association Section beginning in 2018. Robbins received her doctorate in sociology from Columbia University, her M.A. in sociology and anthropology from Tel Aviv University and her B.S.E. in civil engineering and operations research from Princeton University.\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct.\n\n\n\nPlease email rowforwards@gmail.com with any questions, and see here for more information about this workshop series.\nAPPLY NOW!\nWorkshop flyer PDF" }, { - "objectID": "package-dev.html", - "href": "package-dev.html", - "title": "Full Day Package Development Workshop", + "objectID": "edu/york.html", + "href": "edu/york.html", + "title": "Forwards", "section": "", "text": "Forwards is the R Foundation taskforce on women and other under-represented groups and we are offering a free workshop designed for people who use R coding and want to learn more about creating impact from their code. It will cover package contribution and development thus addressing the skills gap that exists within the R and scientific coding community. For example, an analysis of CRAN package maintainers estimated that fewer than 15% were women, and a useR! participant survey found that women were less likely than men to have experience contributing to or writing packages. Whilst these data apply to women, underrepresented groups also include, but are not limited to, LGBTQ+ individuals, and people of colour.\nWorkshop participants will learn to make code into an R package, do collaborative coding with GitHub, write a vignette or an article, build a package web page, and submit a package to CRAN. Participants can bring their own code that they wish to develop into a package or work with a provided example.\n\n\n\nParticipation is free and there is a scholarship program for travel within the UK, child care and other reasonable costs arising from attending the workshop. Scholarships are funded by the R Consortium and a link to the scholarship application form is presented at the end of the workshop application process. In addition, members of the Biochemical Society can apply for a general travel grant to attend the workshop.\nApplication form.\nThe deadline for Scholarship applications is midnight 10 November 2019 with applicants being informed of the outcome on Friday 22 November. 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The deadline for workshop applications is midnight 1 January 2020.\n\n\n\nWorkshop instructors and participants agree to adhere to the R Consortium and R Community Code of Conduct." + }, + { + "objectID": "logo-information.html", + "href": "logo-information.html", + "title": "Forwards logo information", + "section": "", + "text": "The Forwards logo is a derivative of the R logo, ©2016 The R Foundation, used under CC BY-SA 4.0." } ] \ No newline at end of file diff --git a/site_libs/bootstrap/bootstrap.min.css b/site_libs/bootstrap/bootstrap.min.css index 63ecb81e..0abcaa3f 100644 --- a/site_libs/bootstrap/bootstrap.min.css +++ b/site_libs/bootstrap/bootstrap.min.css @@ -3,8 +3,8 @@ * Copyright 2011-2021 The Bootstrap Authors * Copyright 2011-2021 Twitter, Inc. * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE) - */:root{--bs-blue: #007bff;--bs-indigo: #6610f2;--bs-purple: #593196;--bs-pink: #e83e8c;--bs-red: #fc3939;--bs-orange: #fd7e14;--bs-yellow: 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