Discriminating data : correlation, neighborhoods, and the new politics of recognition
Material type:
TextPublication details: London : MIT Press, ©2021Description: xi, 327 p. : ill. ; 24 cmISBN: - 9780262046220
- 005.7 CHU-D
- QA76.9.B45 C57 2021
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IIITD General Stacks | Computer Science and Engineering | 005.7 CHU-D (Browse shelf(Opens below)) | Available | 011027 |
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| 005.7 ACH-B Big data and analytics | 005.7 BAE-M Modern information retrieval | 005.7 CHO-M MongoDB : | 005.7 CHU-D Discriminating data : | 005.7 KEL-D Data science | 005.7 KEP-M Mathematics of big data : | 005.7 KLE-D Designing data-intensive applications : the big ideas behind reliable, scalable, and maintainable systems |
Includes bibliographical references (pages 259-315) and index.
Introduction : how to destroy the world, one solution at a time -- Red pill toxicity, or, Liberation envy -- Correlating eugenics -- The transgressive hypothesis -- Homophily, or, The swarming of the segregated neighborhood -- Proxies, or, reconstructing the unknown -- Algorithmic authenticity -- Correlating ideology, or, What lies at the surface -- Recognizing recognition -- The space between us -- Coda : living in/difference.
"Chun investigates the centrality of race, gender, class, and sexuality to "Big Data" and network analytics"--
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