Date Approved
4-2020
Graduate Degree Type
Thesis
Degree Name
Criminal Justice (M.S.)
Degree Program
School of Criminal Justice
First Advisor
Jacki Cwick
Second Advisor
Chris Kierkus
Third Advisor
Brian Johnson
Academic Year
2019/2020
Abstract
This study assesses the predictive validity of an adult risk need assessment, the Los Angeles Probation Department’s Risk and Needs Assessment Instruments, on 793 clients using several logistic regression models. Models were generated to look for a relationship between risk score and recidivism. This relationship is further explored across gender and race. There are two separate risk assessment instruments used in this study and the sample is separated into two separate groups. The first risk assessment instrument was based on static risk factors such as history of drug or alcohol use, age of first conviction, and conviction history. This assessment was applied to the sample group labeled investigation. The second risk assessment tool incorporated dynamic risk factors such as employment status, education, and peer group. This assessment was applied to the sample group labeled supervision. The results of the study showed that the risk scores calculated in the investigation sample had no significant relationship with recidivism in general or across race or gender. The risk scores calculated in the supervision sample had a significant relationship with recidivism. However, when examined by gender there was no relationship between risk score and recidivism for the female sample. When examined by race there was not a significant relationship between risk score and recidivism in any racial category. Suggestions for implications in practice and future research are also reviewed.
ScholarWorks Citation
Howard, Robert V., "Recidivism, gender, and race: An analysis of the Los Angeles County Probation Department’s Risk and Needs Assessment Instruments" (2020). Masters Theses. 977.
https://scholarworks.gvsu.edu/theses/977
Included in
Criminology and Criminal Justice Commons, Inequality and Stratification Commons, Race and Ethnicity Commons