000			03049cam a2200349 i 4500
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003			BR-SpNIC
005			20230313230210.0
008			191021s2020 maua b 001 0 eng
010			_a 2019036137
020			_a9780262044004 (hardcover)
040			_aLBSOR/DLC _beng _cDLC _erda _dBR-SpNIC
042			_apcc
082	0	0	_a305.42 _223
100	1		_aD'Ignazio, Catherine, _eauthor.
245	1	0	_aData feminism
264		1	_aCambridge, Massachusetts: _bThe MIT Press, _c[2020].
300			_a314 p.:
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		7	_aFeminismo _2Br _93486
650		7	_aFeminismo e ciência _2Br _93487
650		0	_aBig data _xAspectos sociais _9346
650		0	_aPesquisa Qualitativa _xMetodologia _9364
650		0	_aPoder _9756 _xCiências sociais
700	1		_aKlein, Lauren F., _eauthor.
942			_2ddc _cL _k305.42 _mD575
999			_c1504 _d1504