Calculating the Souls of Black Folk

Author:

Abdurahman J. Khadijah

Abstract

In 1995, there were nearly 50,000 children removed from their families into the New York City Administration for Children’s Services’ (ACS) foster care system.1 The NYC ACS’ forcible transfer of children from a protected group into another group may amount to genocide under Article 2(e) of the Genocide Convention if formal review can demonstrate an “intent to destroy” the group “as such” or at least “in part.” Rather than pursuing a citizen’s tribunal, or truth and reconciliation committee to assess the historic transfer of Black children to other groups during this period by the child welfare system, ACS has focused on collecting data from currently targeted populations in order to “predict who needs prevention” services. This paper examines the Family First Prevention Act’s legislative mandate to calculate the “souls of Black folks” and the geographies of predictive analytics developed to serve this aim. Using an abolitionist lens grounded in the epistemology offered by W. E. B. Du Bois’ Souls of Black Folks, this argument moves beyond the Fairness, Accountability and Transparency (FAT) framework to propose strategies for dismantling the “new modes of surveillance and social control” manifested in NYC ACS’ preventive turn. I propose a Get Out mathematics drawing from Katherine McKittrick’s proposal to “count it out different” as the fugitive’s alternative to state sanctioned datafication.

Publisher

Columbia University Libraries

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A computational social science approach to understanding predictors of Chafee service receipt;Children and Youth Services Review;2024-03

2. Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy;ACM Journal on Responsible Computing;2023-12-13

3. The Context of Care: Abstraction Hierarchy Modeling of Therapeutic Foster Care Programs;Journal of Cognitive Engineering and Decision Making;2023-11-03

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