Document Type

Article

Publication Date

12-1-2023

Publication Title

Justice Quarterly

Volume

41

Issue

6

First Page

845

Last Page

869

DOI

https://doi.org/10.1080/07418825.2023.2286238

Abstract

Risk-needs assessments (RNAs) assist correctional staff in assigning supervision and programming. While gender is a well-known predictor of crime, for decades contemporary RNAs have claimed “gender-neutrality” or risk prediction equality for males and females. Unfortunately, females are frequently overclassified, relegated to a category higher than their risks indicate. Using ridge and mixed effects regression methods, we sought to enhance the predictive accuracy of the Modified Positive Achievement Change Tool (MPACT) comparing three common assessment development methods via a 10-state sample of youth (N = 241,596) across multiple justice settings. Findings demonstrated recidivism rates vary substantially by gender and bias/overclassification is likely for assessments using a “gender-neutral” approach. Tools that oversample females, or attempt “equally weighting,” have similar issues. However, “gender-specific” methods create prediction parity, rooting out overclassification. Study takeaways include the need to evaluate tools for overclassification, methods of eliminating gender bias, while achieving strong predictive validity in development of the MPACT.

Comments

This is an Accepted Manuscript of an article published by Taylor & Francis in Justice Quarterly on December 1, 2023, available online: https://doi.org/10.1080/07418825.2023.2286238

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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