Classification for Predicting Recidivism: Challenges and Scopes

In the realm of criminal justice, recidivism pertains to individuals exhibiting persistent patterns of reoffending. This subset of repeat offenders poses a significant burden on the policing system due to its recurring nature. An ability to predict recidivism holds the potential to empower law enforcement with strategic interventions aimed at disrupting this cycle. This study delves into the Recidivism Forecasting Challenge presented by the National Institute of Justice in the Summer of 2021. Two years of data from the State of Georgia and two performance metrics, Brier score and fair and accurate, are used. The data involved a mix of both qualitative and quantitative input variables with potentially complex relationships with the probability of recidivism. In this research, application of a classification model, potential data challenges and scopes are discussed.

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Publication Details

Published
2024-10-01
DOI
https://doi.org/10.21872/2024iise_6000
Primary Topic
Digital and Cyber Forensics
Type
article
Field-Weighted Citation Impact
0.00
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Classification for Predicting Recidivism: Challenges and Scopes

Yuan Zhou, Victoria C. P. Chen, S. S. Rao, Kan Chen et al.
Digital and Cyber Forensics
article

Classification for Predicting Recidivism: Challenges and Scopes

Yuan Zhou, Victoria C. P. Chen, S. S. Rao, Kan Chen, Khan M. A. Haque, Bahareh Nasirian
article en

Abstract

In the realm of criminal justice, recidivism pertains to individuals exhibiting persistent patterns of reoffending. This subset of repeat offenders poses a significant burden on the policing system due to its recurring nature. An ability to predict recidivism holds the potential to empower law enforcement with strategic interventions aimed at disrupting this cycle. This study delves into the Recidivism Forecasting Challenge presented by the National Institute of Justice in the Summer of 2021. Two years of data from the State of Georgia and two performance metrics, Brier score and fair and accurate, are used. The data involved a mix of both qualitative and quantitative input variables with potentially complex relationships with the probability of recidivism. In this research, application of a classification model, potential data challenges and scopes are discussed.

Openalex Percentile: Top 49%
Digital and Cyber Forensics
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