“Data Feminism“ is a groundbreaking exploration of how data science intersects with gender and power dynamics, co-authored by Catherine D’Ignazio and Lauren Klein. This illuminating work delves into the principles of feminist thought, urging a reevaluation of data practices through an inclusive lens. It challenges the status quo of data science, advocating for a more equitable and justice-oriented approach that recognizes and corrects bias. Through compelling examples and insightful analysis, “Data Feminism” empowers readers to rethink the role of data in society, promoting a world where data works for everyone, irrespective of gender.
You can read more about why we chose the book for this years collaborative book review here.
Introduction: Why Data Science Needs Feminism
By Donna Langille
Chapter 1 : The Power Chapter (Principle: Examine Power)
By Parisa Setayesh
Chapter 2 : Collect, Analyze, Imagine, Teach (Principle: Challenge Power)
By Hannah Mendro
Chapter 3 : On Rational, Scientific, Objective Viewpoints from Mythical, Imaginary, Impossible Standpoints (Principle: Elevate Emotion and Embodiment)
Chapter 4 :“What Gets Counted Counts” (Principle: Rethink Binaries and Hierarchies)
By Urmi Parekh
Chapter 5 : Unicorns, Janitors, Ninjas, Wizards, and Rock Stars (Principle: Embrace Pluralism)
Chapter 6 : The Numbers Don’t Speak for Themselves (Principle: Consider Context)
By Abby Cole
Chapter 7 : Show Your Work (Principle: Make Labor Visible)
Conclusion: Now Let’s Multiply
Interview with Catherine D’Ignazio and Lauren Klein authors of Data Feminism(2020)
By Stella Fritzell, Abby Cole, Hamida Khatri & Parisa Setayesh