Classification situations: Life-chances in the neoliberal era

By M. Fourcade, Kieran Healy. 2013

402 citations recorded by the source corpus.

Subfields: Finance

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Citations in the corpus

How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016, methodology): “This shift is made possible by ‘the emergence and expansion of methods of tracking and classifying consumer behavior’ (Fourcade and Healy, 2013: 560).”
Robust Optimization for Fairness with Noisy Protected Groups (2020, background): “” Moreover, the use of the algorithm itself may perpetuate inequity, and in the case of credit scoring, create stratifying effects of economic classifications that shape life-chances [24].”
The Emergence of a Finance Culture in American Households, 1989-2007 (2015, background): “Another alternative emphasizes how the need to engage in financial behavior was spread unevenly across the stratification structure.”
Automated landlord: Digital technologies and post-crisis financial accumulation (2019, background): “These categories carry economic rewards and punishments that contribute to socio-spatial stratification (Fourcade and Healy, 2013, 2017).”
Can we avoid reductionism in risk reduction? (2017, background): “Risk assessments are not only descriptive but constitutive of the social world (Fourcade and Healy, 2013).”
Predatory Inclusion and Education Debt: Rethinking the Racial Wealth Gap (2017, background): “Risk-based pricing by private lenders also means that blacks are more likely offered poorer loan terms than whites on average (Fourcade and Healy 2013; Loonin and Cohen 2008).”
Between Subjectivity and Imposition (2020, background): “With each system’s outcome, meaning is imposed, and higher or lower social positions, chances, and disadvantages are assigned [6, 24, 37, 63].”
The Society of Algorithms (2021, background): “…of gatekeeping rooted in bright lines of inclusion versus exclusion (e.g., those who can obtain credit versus those excluded from it), new algorithmic mechanisms produce a sliding scale of classification situations with a much more fine-grained differentiation of positions (Fourcade & Healy 2013).”
When data is capital: Datafication, accumulation, and extraction (2019, background): “…influence over how businesses and governments behave (Bouk, forthcoming; Fourcade and Healy, 2017; Zuboff, 2016); and (3) data systems are rife with relations of inequity, extraction, and exploitation (Aitken, 2017; Andrejevic, 2014; Fourcade and Healy, 2013; Poon, 2016; Thatcher et al., 2016).”
Democracy of Credit: Ownership and the Politics of Credit Access in Late Twentieth-Century America1 (2016, background): “13 But while the moralization of the creditor-debtor relationship is an old story, what is new and deserves attention here are the techniques through which this moralization operates (Mar-ron 2009; Fourcade and Healy 2013 a ).”
Big Data Surveillance: The Case of Policing (2017, background): “Building on Weber’s concept of class situation, Fourcade and Healy (2013) argue that institutions now use actuarial techniques to track, sort, and categorize individuals into “classification sit-uations” with different rewards and punish-ments attached.”