Merge pull request #40 from alphagov/hs_edit_gitignore

Hs edit gitignore
data-ethics-and-society · Dec 14, 2023 · 1625a5b · 1625a5b
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diff --git a/.gitignore b/.gitignore
@@ -1,43 +1,2 @@
-# History files
-.Rhistory
-.Rapp.history
-
-# Session Data files
-.RData
-
-# User-specific files
-.Ruserdata
-
-# Example code in package build process
-*-Ex.R
-
-# Output files from R CMD build
-/*.tar.gz
-
-# Output files from R CMD check
-/*.Rcheck/
-
-# RStudio files
-.Rproj.user/
-.Rproj
-
-# produced vignettes
-vignettes/*.html
-vignettes/*.pdf
-
-# OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3
-.httr-oauth
-
-# knitr and R markdown default cache directories
-*_cache/
-/cache/
-
-# Temporary files created by R markdown
-*.utf8.md
-*.knit.md
-
-# R Environment Variables
-.Renviron
-
-# IDE
-.idea/
+# VSCode
+.vscode/*
diff --git a/Guides/organising.md b/Guides/organising.md
@@ -6,7 +6,7 @@ We've described how a typical meeting would run in the ['Facilitating'](./facili
 
 ## Deciding on material to read
 
-The [reading list](./../READING-LIST.md) is organised into different sections - some are philosophical, some are technical. Our [previously discussed pieces are available in our Sessions Overview](./../SESSIONS.md). We like to check off things we have discussed [in the reading list](./../READING-LIST.md).  
+The [reading list](./../READING-LIST.md) is organised into different sections - some are philosophical, some are technical. Our [previously discussed pieces are available in our Sessions Overview](./../SESSIONS.md). We like to check off things we have discussed [in the reading list](./../READING-LIST.md).
 
 The whole group votes on what to read for the following meeting at the end of every session. A slido is pre-populated with items already on our reading list, and attendees are invited to vote for items, as well as add anything they want to read for others to upvote.
 
@@ -18,8 +18,8 @@ The whole group votes on what to read for the following meeting at the end of ev
 - [ ] Decide date of next meeting
 - [ ] Create a [meeting information file](./../Sessions/session-template.md) in the `Sessions/` folder
 - [ ] Update the [meeting overview file](./../SESSIONS.md) with a link to the new meeting information page
-- [ ] Create a sign-up form to manage attendees (we currently use the Eventbrite platform for this, but are open to other suggestions)
-- [ ] Produce a Substack post promoting the event
+- [ ] Create a sign-up form to manage attendees (we currently use the Ticket Tailor platform for this, but are open to other suggestions)
+- [ ] Produce a newsletter post promoting the event
 - [ ] Promote the event via the following channels:
   - [ ] #ethics channel of the Cross-Government Data Science Slack Workspace
   - [ ] AnalystX
@@ -36,12 +36,12 @@ The whole group votes on what to read for the following meeting at the end of ev
 - [ ] Set up slido with items pre-populated from the [Reading List](./../READING-LIST.md)
 - [ ] Prepare slides if required
 - [ ] Send a one-week reminder to attendees with a link to the [introductory video](https://www.youtube.com/watch?v=nuWOeRx26iw)
-- [ ] Send a one-day reminder to attendees with quick links to the online meeting  
+- [ ] Send a one-day reminder to attendees with quick links to the online meeting
 
 ### After the meeting
 
 - [ ] Upload [attendee numbers](./../Sessions/attendance.csv)
-- [ ] Update GitHub session pages (e.g. remove session signup links, change icon on reading list)
+- [ ] Update GitHub session pages (e.g. remove session sign-up links, change icon on reading list)
 - [ ] Send thank you email and reminder to vote on slido
 
 ## Contributing

diff --git a/Guides/Format-Guide.md → Guides/session-format.md b/Guides/Format-Guide.md → Guides/session-format.md
diff --git a/Sessions/2020/07-20-session.md b/Sessions/2020/07-20-session.md
@@ -12,7 +12,7 @@ Session 1:  Data Feminism (Chapters 1 - 5)
 
 __Main text:__ Data Feminism [(open review version)](https://bookbook.pubpub.org/data-feminism) (Intro & chapter 1 - 5 only), _Catherine D'Ignazio & Lauren Klein_.
 
-A fully open-access version of this text will soon be available. In th meantime, attendees of the event can be sent a link to a digital version of th text upon request (please email one of the course leaders). Please **do not share** this digital copy of the book outside of the group.
+A fully open-access version of this text will soon be available. In th meantime, attendees of the event can be sent a link to a digital version of th text upon request (please email one of the course leaders). Please _do not share_ this digital copy of the book outside of the group.
 
 #### Supplementary material
 
@@ -25,7 +25,7 @@ __Journal article:__
 
 __Quick read:__
 
-* [Catherine D’Ignazio: 'Data is never a raw, truthful input – and it is never neutral'](https://www.theguardian.com/technology/2020/mar/21/catherine-dignazio-data-is-never-a-raw-truthful-input-and-it-is-never-neutral), _Zoe Corbyn_ for The Guardian 2020 (5 minute read)
+* [Catherine D'Ignazio: 'Data is never a raw, truthful input – and it is never neutral'](https://www.theguardian.com/technology/2020/mar/21/catherine-dignazio-data-is-never-a-raw-truthful-input-and-it-is-never-neutral), _Zoe Corbyn_ for The Guardian 2020 (5 minute read)
 * [Putting Data Back Into Context](https://datajournalism.com/read/longreads/putting-data-back-into-context), _Catherine D'Ignazio_, DataJournalism.com (10 minute read)
 * [“Having Trouble Explaining Oppression? This Comic Can Do It for You](https://everydayfeminism.com/2017/01/trouble-explaining-oppression/) Robot Hugs, 2017 (3 minute read)
 * [The Matrix of Domination and the Four Domains of Power](https://www.blackfeminisms.com/matrix/), Black Feminisms, 2019 (5 minute read)
@@ -70,7 +70,7 @@ General questions might be:
 A few ideas of specific points of discussion, based on the material:
 
 * What does data science mean to you? Does the author's description of data science differ (see below) from your understanding?
-  > “Many people think of data as numbers alone, but data can also consist of words or stories, colors or sounds, or any type of information that is systematically collected, organized, and analyzed. The science in data science simply implies a commitment to systematic methods of observation and experiment.”
+  > “Many people think of data as numbers alone, but data can also consist of words or stories, colors or sounds, or any type of information that is systematically collected, organized, and analyzed (sic). The science in data science simply implies a commitment to systematic methods of observation and experiment.”
   > “...a capacious definition of data science, one that seeks to include rather than exclude and does not erect barriers based on formal credentials, professional affiliation, size of data, complexity of technical methods, or other external markers of expertise.”
 * Is data is the new oil a useful concept?
 * Do we feel this book provides “concrete steps to action for data scientists seeking to learn how feminism can help them work toward justice”?

diff --git a/Sessions/2020/08-20-session.md b/Sessions/2020/08-20-session.md
@@ -17,7 +17,7 @@ Session 2: Reflecting on Practice
 
 __Main text:__ Data Feminism [(open review version)](https://bookbook.pubpub.org/data-feminism), _Catherine D'Ignazio & Lauren Klein_.
 
-A fully open-access version of this text will soon be available. In the meantime, attendees of the event can be sent a link to a digital version of the text upon request (please email one of the course leaders). Please **do not share** this digital copy of the book outside of the group.
+A fully open-access version of this text will soon be available. In the meantime, attendees of the event can be sent a link to a digital version of the text upon request (please email one of the course leaders). Please _do not share_ this digital copy of the book outside of the group.
 
 For this session, please focus on the following selection of supplementary reading material:
 
@@ -28,11 +28,11 @@ __Quick reads:__
 * [We Will Not Allow the Weaponization of COVID-19 Data](https://medium.com/@YESHICAN/we-will-not-allow-the-weaponization-of-covid-19-data-e775d31991c), _Yeshimabeit Milner_, Founder & Executive Director of Data for Black lives (5 minute read)
 * [So, you want to be a feminist data scientist... here's what you need to know](https://data2x.org/so-you-want-to-be-a-feminist-data-scientistheres-what-you-need-to-know/), _Elizabeth Black_ for data2x, 2020 (see also [part 2](https://data2x.org/using-data-feminism-principles-to-create-better-data-infrastructure-and-informed-policies/))
 * [Genetic privacy: We must learn from the story of Henrietta Lacks](https://www.newscientist.com/article/2250449-genetic-privacy-we-must-learn-from-the-story-of-henrietta-lacks/), _Maninder Ahluwalla_ for the New Scientist (5 minute read)
-  
+
 __Gov resources:__
 
 * [Data ethics and AI guidance landscape](https://www.gov.uk/guidance/data-ethics-and-ai-guidance-landscape)
-  
+
 __Journal article:__
 
 * ["Good" isn't good enough](https://www.benzevgreen.com/wp-content/uploads/2019/11/19-ai4sg.pdf), _Ben Green_, NeurIPS Joint Workshop on AI for Social Good, 2019 (15 minute read)

diff --git a/Sessions/2020/09-20-session.md b/Sessions/2020/09-20-session.md
@@ -12,17 +12,17 @@ Session 3:  Data Feminism (Chapters 6+)
 
 __Main text:__ Data Feminism [(open review version)](https://bookbook.pubpub.org/data-feminism) (Chapter 6 onwards), _Catherine D'Ignazio & Lauren Klein_.
 
-A fully open-access version of this text will soon be available. In the meantime, attendees of the event can be sent a link to a digital version of the text upon request (please email one of the course leaders). Please **do not share** this digital copy of the book outside of the group.
+A fully open-access version of this text will soon be available. In the meantime, attendees of the event can be sent a link to a digital version of the text upon request (please email one of the course leaders). Please _do not share_ this digital copy of the book outside of the group.
 
 #### Supplementary material
 
 If you cannot obtain a copy of Data Feminism, or wish to continue your reading outside of the core material, below is a selection of supplementary reading material.
 
 __Quick read:__
 
-* [Catherine D’Ignazio: 'Data is never a raw, truthful input – and it is never neutral'](https://www.theguardian.com/technology/2020/mar/21/catherine-dignazio-data-is-never-a-raw-truthful-input-and-it-is-never-neutral), _Zoe Corbyn_ for The Guardian 2020 (5 minute read)
+* [Catherine D'Ignazio: 'Data is never a raw, truthful input – and it is never neutral'](https://www.theguardian.com/technology/2020/mar/21/catherine-dignazio-data-is-never-a-raw-truthful-input-and-it-is-never-neutral), _Zoe Corbyn_ for The Guardian 2020 (5 minute read)
 * [Putting Data Back Into Context](https://datajournalism.com/read/longreads/putting-data-back-into-context), _Catherine D'Ignazio_, DataJournalism.com (10 minute read)
-  
+
 __Journal articles:__
 
 * Ford, Heather & Wajcman, Judy. (2017). [‘Anyone can edit’, not everyone does: Wikipedia's infrastructure and the gender gap](https://www.researchgate.net/publication/311769445_%27Anyone_can_edit%27_not_everyone_does_Wikipedia%27s_infrastructure_and_the_gender_gap). Social Studies of Science. 47. 10.1177/0306312717692172. (25 minute read)
@@ -64,7 +64,7 @@ A few ideas of specific points of discussion, based on the material:
 * Can an 'engaged' and thoughtful data science practitioner in government actually make change?
 * Should we think critically about 'public good' as civil servants?
 * Is working through a lens of intersectional feminism in direct conflict with public sector 'neutrality'?
-  
+
 #### Specific discussion points for Chapters 6+ of Data Feminism for civil servants
 
 * Is there 'hidden labour' involved in data science practice in the civil service?

diff --git a/Sessions/2021/03-21-session.md b/Sessions/2021/03-21-session.md
@@ -43,7 +43,7 @@ These are not pre-requisite reading material for attendance, but a compilation o
 
 ## Questions for discussion
 
-### Related to  [Ababa Bihrane 's paper on Algorithmic injustice: a relational ethics approach](https://www.sciencedirect.com/science/article/pii/S2666389921000155)
+### Related to  [Abeba Birhane 's paper on Algorithmic injustice: a relational ethics approach](https://www.sciencedirect.com/science/article/pii/S2666389921000155)
 
 1. How can we leverage data practices in order to gain an in-depth understanding of certain problems as situated in structural inequalities and oppression (e.g. Institutional racism as defined by MacPherson Report)?”
 2. How might a data worker engage vulnerable communities in ways that surface harms, when it is often the case that algorithmic harms may be secondary effects, invisible to designers and communities alike, and what questions might be asked to help anticipate these harms?”

diff --git a/Sessions/2021/07-21-session.md b/Sessions/2021/07-21-session.md
@@ -10,7 +10,7 @@ This time we're going to discuss the **first three chapters** (Earth, Labor & Da
 
 Atlas of AI presents AI as a technology of extraction: from the minerals drawn from the earth, to the labour pulled from low-wage information workers, to the data taken from every action and expression.
 
-This book can be purchased in the UK from [Blackwell's](https://blackwells.co.uk/bookshop/product/Atlas-of-AI-by-Kate-Crawford-author/9780300209570), [AbeBooks](https://www.abebooks.co.uk/9780300209570/Atlas-Power-Politics-Planetary-Costs-0300209576/plp), [Amazon](https://www.amazon.co.uk/Atlas-AI-Kate-Crawford/dp/0300209576/ref=sr_1_1) (kindle or hardcover), or an independent retailer.
+This book can be purchased in the UK from [Blackwell's](https://blackwells.co.uk/bookshop/product/Atlas-of-AI-by-Kate-Crawford-author/9780300209570), [AbeBooks](https://www.abebooks.co.uk/9780300209570/Atlas-Power-Politics-Planetary-Costs-0300209576/plp), [Amazon](https://www.amazon.co.uk/Atlas-AI-Kate-Crawford/dp/0300209576/ref=sr_1_1) (kindle or hardback), or an independent retailer.
 
 #### **You are very welcome to attend if you haven't read any of the book**
 

diff --git a/Sessions/2021/08-21-session.md b/Sessions/2021/08-21-session.md
@@ -10,7 +10,7 @@ Following our successful event looking at the first three chapters (Earth, Labor
 
 Atlas of AI presents AI as a technology of extraction: from the minerals drawn from the earth, to the labour pulled from low-wage information workers, to the data taken from every action and expression.
 
-This book can be purchased in the UK from [Blackwell's](https://blackwells.co.uk/bookshop/product/Atlas-of-AI-by-Kate-Crawford-author/9780300209570), [AbeBooks](https://www.abebooks.co.uk/9780300209570/Atlas-Power-Politics-Planetary-Costs-0300209576/plp), [Amazon](https://www.amazon.co.uk/Atlas-AI-Kate-Crawford/dp/0300209576/ref=sr_1_1) (kindle or hardcover), or an independent retailer.
+This book can be purchased in the UK from [Blackwell's](https://blackwells.co.uk/bookshop/product/Atlas-of-AI-by-Kate-Crawford-author/9780300209570), [AbeBooks](https://www.abebooks.co.uk/9780300209570/Atlas-Power-Politics-Planetary-Costs-0300209576/plp), [Amazon](https://www.amazon.co.uk/Atlas-AI-Kate-Crawford/dp/0300209576/ref=sr_1_1) (kindle or hardback), or an independent retailer.
 
 #### **You are very welcome to attend if you haven't read any of the book. You are also welcome if you didn't attend the first event!**
 
@@ -26,7 +26,7 @@ Contains a lot of similar material to that covered in the 'Classification' chapt
 This article is adapted from the book's 'Affect' chapter.
 
 - [Google’s artificial intelligence ethics won't curb war by algorithm](https://www.wired.co.uk/article/google-project-maven-drone-warfare-artificial-intelligence), *Phoebe Braithwaite, Wired*.
-This article explores how Google was involved with the  US Department of Defense’s Project Maven, which used AI to target drone strikes.
+This article explores how Google was involved with the  US Department of Defense's Project Maven, which used AI to target drone strikes.
 
 - [Stop talking about AI ethics. It’s time to talk about power](https://www.technologyreview.com/2021/04/23/1023549/kate-crawford-atlas-of-ai-review/), *Karen Hao, MIT Technology Review*.
 This is a review article for the book, which summarises everything neatly.

diff --git a/Sessions/2023/12-23-session.md b/Sessions/2023/12-23-session.md
@@ -4,7 +4,7 @@
 
 ## Description
 
-You're welcome to join us for our next Data Ethics & Society Reading Group on Thursday 14th December at [12:00 GMT](https://www.timeanddate.com/worldclock/fixedtime.html?msg=Escape+from+Model+Land-+Data+Ethics+and+Society+Reading+Group&iso=20231214T12&p1=303&ah=1). 
+You're welcome to join us for our next Data Ethics & Society Reading Group on Thursday 14th December at [12:00 GMT](https://www.timeanddate.com/worldclock/fixedtime.html?msg=Escape+from+Model+Land-+Data+Ethics+and+Society+Reading+Group&iso=20231214T12&p1=303&ah=1).
 
 This time we're going to read [Escape from Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do about It](https://www.ericathompson.co.uk/books/) by Dr Erica Thompson, who, drawing on contemporary examples from finance, climate and health policy, explores what models are, why we need them, how they work and what happens when they go wrong.