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Highly recommend Data Feminism by Catherine D'Ignazio @kanarinka and Lauren Klein @laurenfklein.
What a powerful and important book!
Some excerpts in the
to hopefully convince some of you to read the book.
What a powerful and important book!
Some excerpts in the
to hopefully convince some of you to read the book.
Data Feminism brings an intersectional feminist perspective to data science.
One of the most important recurring theme is co-liberation. Specifically, going from "data for good" to co-liberation.
“If you have come here to help me you are wasting your time, but if you have come because your liberation is bound up with mine, then let us work together.”
“If you have come here to help me you are wasting your time, but if you have come because your liberation is bound up with mine, then let us work together.”
The importance of lived experience is highlighted throughout the book. One of the most important discussion about lived experience is in the context of the 'privileged hazard' — those who occupy privileged positions are bad at recognizing oppression.
An example of such systems is the TSA scanner which hard codes the trans phobia of designers.
Also checkout this wonderful post by Sasha Costanza-Chock @schock. They discuss the matrix of domination, design justice, and more. (also h/t @PDez90)
https://jods.mitpress.mit.edu/pub/costanza-chock/release/4
Also checkout this wonderful post by Sasha Costanza-Chock @schock. They discuss the matrix of domination, design justice, and more. (also h/t @PDez90)
https://jods.mitpress.mit.edu/pub/costanza-chock/release/4
Another recurring theme is the importance of plurality of voices. The seriousness of the authors about this is clearly reflected in their meticulous documentation of their own references (both aspirational and what was published).
Perhaps may of us will be most thankful to the authors for coining the term #BigDickData!
This thread is far from a summary of the book. In fact, I have violated an important principle of feminist thinking — all knowledge is situated (context matters). Many of these excerpts are without/outside their original context.
So, please buy the book and read it!
So, please buy the book and read it!
