000 03300cam a2200409 i 4500
001 21273441
003 OSt
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008 191021s2020 maua b 001 0 eng
010 _a 2019036137
020 _a9780262044004
_q(hardcover)
035 _a21273441
040 _aLBSOR/DLC
_beng
_cDLC
_erda
_dDLC
042 _apcc
050 0 0 _aHQ1190
_b.D574 2020
082 0 0 _a305.42
_223
100 1 _aD'Ignazio, Catherine,
_eauthor.
245 1 0 _aData feminism /
_cCatherine D'Ignazio and Lauren F. Klein.
264 1 _aCambridge, Massachusetts :
_bThe MIT Press,
_c[2020]
300 _axii, 314 pages :
_billustrations (some color) ;
_c24 cm.
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
490 0 _aStrong ideas series
504 _aIncludes bibliographical references (pages 235-301) and index.
505 0 _aIntroduction: 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.
520 _a"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 justice. This book takes a stand against a world that benefits some (including the authors, two white women) at the expense of others. It seeks to provide concrete steps for data scientists seeking to learn how feminism can help them work towards justice, and for feminists seeking to learn how their own work can carry over to the growing field of data science. It is addressed to professionals in all fields where data-driven decisions are being made, as well as to communities that want to better understand the data that surrounds them. It is written for everyone who seeks to better understand the charts and statistics that they encounter in their day-to-day lives, and for everyone who seeks to better communicate the significance of such charts and statistics to others. This is an example-driven book written with a broad audience of scholars, students, and practitioners in mind. It offers a way of thinking about data, both their uses and their limits, that is informed by direct experience, by a commitment to action, and by the ideas associated with intersectional feminist thought"--
_cProvided by publisher.
650 0 _aFeminism.
650 0 _aFeminism and science.
650 0 _aBig data
_xSocial aspects.
650 0 _aQuantitative research
_xMethodology
_xSocial aspects.
650 0 _aPower (Social sciences)
700 1 _aKlein, Lauren F.,
_eauthor.
906 _a7
_bcbc
_corignew
_d1
_eecip
_f20
_gy-gencatlg
942 _2lcc
_cBK
_n0
999 _c21775
_d21775