Computational Model Library

Youth and their Artificial Social Environmental Risk and Promotive Scores (Ya-TASERPS) (1.0.0)

Risk assessments are designed to measure cumulative risk and promotive factors for delinquency and recidivism, and are used by criminal and juvenile justice systems to inform sanctions and interventions. Yet, these risk assessments tend to focus on individual risk and often fail to capture each individual’s environmental risk. This agent-based model (ABM) explores the interaction of individual and environmental risk on the youth. The ABM is based on an interactional theory of delinquency and moves beyond more traditional statistical approaches used to study delinquency that tend to rely on point-in-time measures, and to focus on exploring the dynamics and processes that evolve from interactions between agents (i.e., youths) and their environments. Our ABM simulates a youth’s day, where they spend time in schools, their neighborhoods, and families. The youth has proclivities for engaging in prosocial or antisocial behaviors, and their environments have likelihoods of presenting prosocial or antisocial opportunities.

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Release Notes

This is the first release.

Associated Publications

Lee, J.S. & Crooks, A.T. (accepted). Youth and their artificial social environmental risk and promotive scores (Ya-TASERPS). Journal of Artificial Societies and Social Simulation.

This release is out-of-date. The latest version is 1.1.0

Youth and their Artificial Social Environmental Risk and Promotive Scores (Ya-TASERPS) 1.0.0

Risk assessments are designed to measure cumulative risk and promotive factors for delinquency and recidivism, and are used by criminal and juvenile justice systems to inform sanctions and interventions. Yet, these risk assessments tend to focus on individual risk and often fail to capture each individual’s environmental risk. This agent-based model (ABM) explores the interaction of individual and environmental risk on the youth. The ABM is based on an interactional theory of delinquency and moves beyond more traditional statistical approaches used to study delinquency that tend to rely on point-in-time measures, and to focus on exploring the dynamics and processes that evolve from interactions between agents (i.e., youths) and their environments. Our ABM simulates a youth’s day, where they spend time in schools, their neighborhoods, and families. The youth has proclivities for engaging in prosocial or antisocial behaviors, and their environments have likelihoods of presenting prosocial or antisocial opportunities.

Release Notes

This is the first release.

Version Submitter First published Last modified Status
1.1.0 JoAnn Lee Fri Feb 24 21:41:06 2023 Fri Feb 24 21:41:47 2023 Published
1.0.0 JoAnn Lee Wed Jul 7 14:43:16 2021 Fri Feb 24 21:39:29 2023 Published

Discussion

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