New Tool Improves Teen Recidivism Prediction

2005 ◽  
Vol 33 (3) ◽  
pp. 54
Author(s):  
BRUCE JANCIN
Author(s):  
William T. Miller ◽  
Christina A. Campbell ◽  
Jordan Papp ◽  
Ebony Ruhland

Scholars have presented concerns about potential for racial bias in risk assessments as a result of the inclusion of static factors, such as criminal history in risk assessments. The purpose of this study was to examine the extent to which static factors add incremental validity to the dynamic factors in criminogenic risk assessments. This study examined the Youth Level of Service/Case Management Inventory (YLS/CMI) in a sample of 1,270 youth offenders from a medium-sized Midwestern county between June 2004 and November 2013. Logistic regression was used to determine the predictive validity of the YLS/CMI and the individual contribution of static and dynamic domains of the assessment. Results indicated that the static domain differentially predicted recidivism for Black and White youth. In particular, the static domain was a significant predictor of recidivism for White youth, but this was not the case for Black youth. The dynamic domain significantly predicted recidivism for both Black and White offenders, and static risk factors improved prediction of recidivism for White youth, but not for Black youth.


2011 ◽  
Vol 38 (8) ◽  
pp. 840-853 ◽  
Author(s):  
Eyitayo Onifade ◽  
Jodi Petersen ◽  
Timothy S. Bynum ◽  
William S. Davidson

Risk assessments such as the Youth Level of Service/Case Management Inventory (YLS/CMI) that predict delinquency outcomes based on proximal risk factors may benefit from an incorporation of distal risk factors in their prediction models. This study utilized a juvenile probationer sample and block group SES data in exploring the differential predictive validity of the YLS/CMI with youth of similar person-centered risk levels from different criminogenic neighborhood types. The study entailed an exploratory factor analysis of block group socioeconomic variables, which were used in a cluster analysis to create criminogenic neighborhood typology system. Hierarchical logistic regression was used to analyze the relationship among recidivism (Level 1), risk score (Level 1), neighborhood SES factors (Level 2), and neighborhood types (Level 2). Significant interactions were found across levels among variables, suggesting the risk—recidivism relationship was moderated by neighborhood socioeconomic ecology. Implications for practice and policy are discussed.


1996 ◽  
Vol 6 (4) ◽  
pp. 349-359 ◽  
Author(s):  
Don Grubin ◽  
Sarah Wingate

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Cynthia Rudin ◽  
Caroline Wang ◽  
Beau Coker

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