Risk, race, and predictive policing
A critical race theory analysis of the strategic subject list
Dados Bibliográficos
| ID | 11054705 |
|---|---|
| Autores | Andrea L DaViera (0000-0003-4235-0597, Psychology Department University of Illinois Chicago Chicago Illinois USA, autor correspondente), Marbella Uriostegui (0000-0001-6225-598X, Applied Research & Equitable Evaluation Education Northwest Portland Oregon USA), Aaron Gottlieb (0000-0001-9018-2263, Crown Family School of Social Work, Policy, and Practice University of Chicago Chicago Illinois USA), Ogechi “cynthia” Onyeka (0000-0002-9110-2090, Psychiatry & Behavioral Sciences Baylor College of Medicine Houston Texas USA) |
| Ano | 2024 |
| Volume | 73 |
| Fascículo | 1-2 |
| Páginas | 91-103 |
| Data de publicação | 2024-03-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | American Journal of Community Psychology (JOURNAL) |
| Identificadores do periódico | ISSN: 0091-0562 • E-ISSN: 1573-2770 |
| Editora | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/ajcp.12671 |
| PMID | 37067014 |
| OpenAlex | W4366083553 |
| Idioma | EN |
| Citações recebidas | 5 |
| Referências citadas | 49 |
Predictive policing is a tool used increasingly by police departments that may exacerbate entrenched racial/ethnic disparities in the Prison Industrial Complex (PIC). Using a Critical Race Theory framework, we analyzed arrest data from a predictive policing program, the Strategic Subject List (SSL), and questioned how the SSL risk score (i.e., calculated risk for gun violence perpetration or victimization) predicts the arrested individual's race/ethnicity while accounting for local spatial conditions, including poverty and racial composition. Using multinomial logistic regression with community area fixed effects, results indicate that the risk score predicts the race/ethnicity of the arrested person while accounting for spatial context. As such, despite claims of scientific objectivity, we provide empirical evidence that the algorithmically‐derived risk variable is racially biased. We discuss our study in the context of how the SSL reinforces a pseudoscientific justification of the PIC and call for the abolition of these tools broadly
Criminology · Health psychology · Public health · Race (biology) · Sociology · Subject (documents) · Computer Science · Crime Patterns and Interventions · Gender Studies · Medicine · Policing Practices and Perceptions · Psychology · Social and Intergroup Psychology · Social Psychology
Digitize and Punish
Predictions put into practice
Layers of Bias
The criminogenic and psychological effects of police stops on adolescent black and Latino boys
Predictive Policing
Black Bodies on the Ground
The Criminal Law and Law Enforcement Implications of Big Data
Conceptualizing color-evasiveness
QuantCrit
QuantCrit
The Interaction of Race and Gender as a Significant Driver of Racial Arrest Disparities for African American Men
Using QuantCrit to Advance an Anti-Racist Developmental Science
Don’t Ever Forget Now, You’re a Black Man in America”
The effect of direct and vicarious police contact on the educational achievement of urban teens
Critical Race Theory and Criminal Justice
Identifying abolitionist alignments in community psychology
The Cumulative Probability of Arrest by Age 28 Years in the United States by Disability Status, Race/Ethnicity, and Gender
The neighborhood context of racial and ethnic disparities in arrest
Bringing abolition in
The Legacy of Slavery and Mass Incarceration
Effect of Suspect Race on Officers’ Arrest Decisions
Producing race disparities
Examining Racial Disparities in Drug Arrests
Intersectional Criminologies for the Contemporary Moment
Nobody trusts them! Under- and over-policing Native American Communities
Living under surveillance
Big Data Surveillance
Predictable Policing
Arrested by Skin Color
Association of Skin Color and Generation on Arrests Among Mexican-Origin Latinos
The Linguistics of Color Blind Racism
Geographies of death
The color of punishment
| Obras citantes distintas | 5 |
|---|---|
| Citações por ano | 2,5 |
| Intervalo de citações | 2024 - 2025 (2) |
| Velocidade de citação | recent |
| Altamente citado | Não |
| Tipos de citação | Neutras: 5 |