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Data feminism / Catherine D'Ignazio and Lauren F. Klein.

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"We have seen through many examples that data science and artificial intelligence can reinforce structural inequalities like sexism and racism. Data is power, and that power is distributed unequally. This book offers a vision for a feminist data science that can challenge power and work towards...

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Bibliographic Details
Main Authors: Kanarinka (Author), Klein, Lauren F. (Author)
Format: Book
Language:English
Published: Cambridge, Massachusetts : The MIT Press, [2020]
Series:ideas series.
Subjects:
Feminism.
Feminism and science.
Big data > Social aspects.
Quantitative research > Methodology > Social aspects.
Power (Social sciences)
Table of Contents:
  • Introduction: Why data science needs feminism
  • Examine power : the power chapter
  • Challenge power : collect, analyze, imagine, teach
  • Elevate emotion and embodiment : on rational, scientific, objective viewpoints from mythical, imaginary, impossible standpoints
  • Rethink binaries and hierarchies : "What gets counted counts"
  • Embrace pluralism : unicorns, janitors, ninjas, wizards and rock stars
  • Consider context : the numbers don't speak for themselves
  • Make labor visible : show your work
  • Conclusion: Now let's multiply.

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