Data feminism [electronic resource]

상세정보

자료유형	단행본
서명/저자사항	Data feminism [electronic resource] / Catherine D'Ignazio and Lauren F. Klein.
개인저자	D'Ignazio, Catherine, author. Klein, Lauren F., author.
발행사항	Cambridge, Massachusetts: The MIT Press, 2020,c2020
형태사항	1 online resource (xii, 314 pages) : color illustrations
총서사항	<strong> ideas series
ISBN	0262358522 9780262358521
서지주기	Includes bibliographical references (235-301) and indexes.
내용주기	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.
요약	A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom Data science for whom Data science with whose interests in mind The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics--one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever "speak for themselves." Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.
일반주제명	Feminism. Feminism and science. Big data --Social aspects. Quantitative research --Methodology --Social aspects. Power (Social sciences) Big data --Social aspects. Feminism. Feminism and science. Power (Social sciences)
분류기호(DDC)	305.42
언어	영어
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