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41 Just. Q. 845 (2024)
Comparing Meters to Yards: A Nationally Representative Evaluation of Gender Bias in Risk Assessment

handle is hein.journals/jquart41 and id is 916 raw text is: JUSTICE QUARTERLY 2024, VOL. 41, NO. 6, 845-869 https://doi.org/10.1080/07418825.2023.2286238 A RgRoutledge Taylor&FrancisGroup Checkk~r updates Comparing Meters to Yards: A Nationally Representative Evaluation of Gender Bias in Risk Assessment Zachary Hamiltona, Melissa Kowalskib, Michael Campagnaa, Addison Kobiea and Alex Kigerla aUniversity of Nebraska-Omaha, Omaha, Nebraska, USA; bWisconsin Department of Corrections, Madison, Wisconsin, USA ABSTRACT ARTICLE HISTORY Risk-needs assessments (RNAs) assist correctional staff in assigning Received 7 June 2023 supervision and programming. While gender is a well-known pre- Accepted 15 November dictor of crime, for decades contemporary RNAs have claimed 2023 gender-neutrality or risk prediction equality for males and females. KEYWORDS Unfortunately, females are frequently overclassified, relegated to a Juvenile justice; risk-need category higher than their risks indicate. Using ridge and mixed assessment; recidivism; effects regression methods, we sought to enhance the predictive bias; prediction 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 multi- ple justice settings. Findings demonstrated recidivism rates vary substantially by gender and bias/overclassification is likely for assessments using a gender-neutral approach. Tools that oversam- ple females, or attempt equally weighting, have similar issues. However, gender-specific methods create prediction parity, root- ing out overclassification. Study takeaways include the need to evaluate tools for overcdassification, methods of eliminating gender bias, while achieving strong predictive validity in development of the MPACT Introduction Risk-needs assessments (RNAs) are tools commonly used by justice agencies to stan- dardize intervention provision, wherein individuals with the same risk score possess the same probability of recidivism and hence, should receive a similar level of super- vision and programming. RNAs traditionally gather offense history and use semi-structured interviews to score individuals risks of recidivism, which are then summed to create a composite risk score. Thresholds (or cut points) are then set to divide the scale's distribution to form risk level categories (RLCs). The Risk-Need- Responsivity (RNR) model outlines the use of RLCs, where higher risk individuals are to receive a greater intensity of supervision and programming, while lower risk CONTACT Zachary Hamilton ® zhamilton@unomaha.edu 0 Supplemental data for this article can be accessed online at https://doi.org/10.1080/07418825.2023.2286238. © 2023 Academy of Criminal Justice Sciences

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