Introduction : Why data science needs feminism --
The power chapter ; Principle: Examine power --
Collect, analyze, imagine, teach ; Principle: Challenge power--
On rational, scientific, objective viewpoints from mythical, imaginary, impossible standpoints ; Principle: Elevate emotion and embodiment --
"What gets counted counts" ; Principle: Rethink binaries and hierarchies --
Unicorns, janitors, ninja, wizards, and rock stars ; Principle: Embrace pluralism --
The numbers don't speak for themselves ; Principle: Consider context--
Show your work ; Principle: Make labor visible --
Conclusion : now let's multiply; Our values and our metrics for holding ourselves accountable ; Auditing Data Feminism / Isabel Carter.
