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040			_aLBSOR/DLC _bspa _cDLC _erda _dUIASF
050		4	_aHQ 1190 _bD574.2020
100	1		_aD'Ignazio, Catherine _eautor
245	1	0	_aData feminism / _cCatherine D'Ignazio and Lauren F. Klein.
264		1	_aCambridge, Massachusetts : _bThe MIT Press, _c[2020],
264		4	_c©2020.
300			_axii, 314 páginas : _bilustraciones (algunas a color) ; _c24 cm.
336			_atexto _btxt _2rdacontent
337			_asin mediación _bn _2rdamedia
338			_avolumen _bnc _2rdacarrier
490	0		_aStrong ideas series
504			_aIncluye referencias bibliográficas (páginas 235-301) e índice.
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"-- _cEditorial.
650		0	_aFeminism
650		4	_aFeminismo _9171794
650		0	_aFeminism and science
650		4	_aFeminismo y ciencia
650		0	_aBig data _xSocial aspects
650		4	_aBig data _xAspectos sociales
650		0	_aQuantitative research _xMethodology _xSocial aspects
650		4	_aInvestigación cuantitativa _xMetodología _xAspectos sociales
650		0	_aPower (Social sciences)
650		4	_aPoder (Ciencias sociales) _9378
700	1		_aKlein, Lauren F., _eautor
942			_2lcc _cNEWBFXC1
980			_6128864 _aLAURA CAROLINA CARROUCHE SILVA _8128854 _gVICTOR DE LA MORA MEDINA
999			_c703370 _d703370