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Racial formations as data formations
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Phan, Thao and Wark, Scott (2021) Racial formations as data formations. Big Data & Society, 8 (2). pp. 1-5. doi:10.1177/20539517211046377
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Official URL: https://doi.org/10.1177/20539517211046377
Abstract
This commentary uses Paul Gilroy’s controversial claim that new technoscientific processes are instituting an ‘end to race’ as a provocation to discuss the epistemological transformation of race in algorithmic culture. We situate Gilroy’s provocation within the context of an abolitionist agenda against racial-thinking, underscoring the relationship between his post-race polemic and a post-visual discourse. We then discuss the challenges of studying race within regimes of computation, which rely on structures that are, for the most part, opaque; in particular, modes of classification that operate through proxies and abstractions and that figure racialized bodies not as single, coherent subjects, but as shifting clusters of data. We argue that in this new regime, race emerges as an epiphenomenon of processes of classifying and sorting – what we call ‘racial formations as data formations’. This discussion is significant because it raises new theoretical, methodological and political questions for scholars of media and critical algorithmic studies. It asks: how are we supposed to think, to identify and to confront race and racialisation when they vanish into algorithmic systems that are beyond our perception? What becomes of racial formations in post-visual regimes?
Item Type: | Journal Item | |||||||||
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Subjects: | H Social Sciences > HT Communities. Classes. Races Q Science > QA Mathematics T Technology > TA Engineering (General). Civil engineering (General) |
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Divisions: | Faculty of Social Sciences > Centre for Interdisciplinary Methodologies | |||||||||
SWORD Depositor: | Library Publications Router | |||||||||
Library of Congress Subject Headings (LCSH): | Gilroy, Paul, 1956-, Post-racialism -- Data processing, Multiculturalism, Race, Algorithms, Artificial intelligence | |||||||||
Journal or Publication Title: | Big Data & Society | |||||||||
Publisher: | SAGE Publications | |||||||||
ISSN: | 2053-9517 | |||||||||
Official Date: | 1 July 2021 | |||||||||
Dates: |
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Volume: | 8 | |||||||||
Number: | 2 | |||||||||
Number of Pages: | 5 | |||||||||
Page Range: | pp. 1-5 | |||||||||
DOI: | 10.1177/20539517211046377 | |||||||||
Status: | Peer Reviewed | |||||||||
Publication Status: | Published | |||||||||
Reuse Statement (publisher, data, author rights): | * | |||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||
Date of first compliant deposit: | 27 October 2021 | |||||||||
Date of first compliant Open Access: | 27 October 2021 | |||||||||
RIOXX Funder/Project Grant: |
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