What Risk-Assessment Instruments Reveal About Racial Disparities: Examining Outcomes and Intervention Needs of Male Juvenile Offenders

2011 ◽  
Author(s):  
Christina A. Campbell ◽  
Jodi L. Petersen ◽  
Eyitayo Onifade ◽  
William S. Davidson
Keyword(s):  
Risk Assessment ◽  
Juvenile Offenders ◽  
Racial Disparities ◽  
Assessment Instruments

Racist Algorithms or Systemic Problems? Risk Assessments and Racial Disparities

2020 ◽  
Vol 47 (12) ◽  
pp. 1576-1584
Author(s):  
Gina M. Vincent ◽  
Jodi L. Viljoen
Keyword(s):  
Risk Assessment ◽  
Racial Disparities ◽  
Justice System ◽  
Racial Bias ◽  
Ethnic Disparities ◽  
Risk Assessments ◽  
Assessment Instruments ◽  
Racial And Ethnic Disparities ◽  
Prediction Of Recidivism ◽  
Systemic Problems

As recent and historical events attest, racial and ethnic disparities are widely engrained into the justice system. Recently, scholars and policymakers have raised concerns that risk assessment instruments may exacerbate these disparities. While it is critical that risk instruments be scrutinized for racial bias, some concerns, though well-meaning, have gone beyond the evidence. This article explains what it means for an instrument to be “biased” and why instruments should not all be painted with the same brush (some will be more susceptible to bias than others). If some groups get apprehended more, those groups will score higher on non-biased, well-validated instruments derived to maximize prediction of recidivism because of mathematics. Thus, risk instruments shine a light on long-standing systemic problems of racial disparities. This article concludes with suggestions for research and for minimizing disparities by ensuring that systems use risk assessments to avoid unnecessary incarceration while allowing for structured discretion.

Predictive Validity of the Joint Risk Matrix With Juvenile Offenders

2007 ◽  
Vol 34 (3) ◽  
pp. 348-361 ◽  
Author(s):  
Craig S. Schwalbe ◽  
Mark W. Fraser ◽  
Steven H. Day
Keyword(s):  
Risk Assessment ◽  
Juvenile Offenders ◽  
Juvenile Justice ◽  
Predictive Validity ◽  
Juvenile Justice System ◽  
Assessment Instruments ◽  
Risk Matrix ◽  
Race Ethnicity ◽  
Actuarial Risk ◽  
Gender Based

Actuarial risk assessment instruments promise to increase decision-making accuracy and equity in settings such as the juvenile justice system, but both aims presume high levels of predictive validity. Prior research suggests that the predictive validity of some juvenile justice risk assessment instruments differs across gender and race/ethnicity. The Joint Risk Matrix (JRM) described herein is an instrument developed to increase the predictive validity of risk assessment for the diverse populations served by the nation’s juvenile courts. The predictive validity of the JRM was estimated on a sample of 536 court-involved juveniles. The instrument demonstrated acceptable levels of validity across all juveniles (AUC = .710). Gender-based differences were explained by gendered patterns of referral to out-of-home placements. Differences by race/ethnicity were reduced compared with previous reports. The findings suggest that risk assessment can be improved by including measures related to the behavior and demeanor of offenders and the cooperation of their parents or caretakers.

Evaluating risk assessment instruments for intimate partner stalking and intimate partner violence.

2018 ◽  
Vol 5 (2) ◽  
pp. 103-118 ◽  
Author(s):  
Jacomina Gerbrandij ◽  
Barry Rosenfeld ◽  
Alicia Nijdam-Jones ◽  
Michele Galietta
Keyword(s):  
Risk Assessment ◽  
Intimate Partner Violence ◽  
Partner Violence ◽  
Intimate Partner ◽  
Assessment Instruments

scholarly journals Rates of violence in patients classified as high risk by structured risk assessment instruments

2014 ◽  
Vol 204 (3) ◽  
pp. 180-187 ◽  
Author(s):  
Jay P. Singh ◽  
Seena Fazel ◽  
Ralitza Gueorguieva ◽  
Alec Buchanan
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Risk Groups ◽  
Evidence Base ◽  
Assessment Tools ◽  
Current Evidence ◽  
Assessment Instruments ◽  
Individual Liberty ◽  
Current Evidence Base ◽  
Study Heterogeneity

BackgroundRates of violence in persons identified as high risk by structured risk assessment instruments (SRAIs) are uncertain and frequently unreported by validation studies.AimsTo analyse the variation in rates of violence in individuals identified as high risk by SRAIs.MethodA systematic search of databases (1995–2011) was conducted for studies on nine widely used assessment tools. Where violence rates in high-risk groups were not published, these were requested from study authors. Rate information was extracted, and binomial logistic regression was used to study heterogeneity.ResultsInformation was collected on 13 045 participants in 57 samples from 47 independent studies. Annualised rates of violence in individuals classified as high risk varied both across and within instruments. Rates were elevated when population rates of violence were higher, when a structured professional judgement instrument was used and when there was a lower proportion of men in a study.ConclusionsAfter controlling for time at risk, the rate of violence in individuals classified as high risk by SRAIs shows substantial variation. In the absence of information on local base rates, assigning predetermined probabilities to future violence risk on the basis of a structured risk assessment is not supported by the current evidence base. This underscores the need for caution when such risk estimates are used to influence decisions related to individual liberty and public safety.

Evidence-Based Sentencing

Criminology ◽  
2021 ◽  
Author(s):  
James C. Oleson
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Risk Measures ◽  
Criminal History ◽  
Community Safety ◽  
Assessment Instruments ◽  
Evidence Based ◽  
Criminogenic Needs ◽  
Actuarial Risk ◽  
Using Data

The evidence-based practice (EBP) movement can be traced to a 1992 article in the Journal of the American Medical Association, although decision-making with empirical evidence (rather than tradition, anecdote, or intuition) is obviously much older. Neverthless, for the last twenty-five years, EBP has played a pivotal role in criminal justice, particularly within community corrections. While the prediction of recidivism in parole or probation decisions has attracted relatively little attention, the use of risk measures by sentencing judges is controversial. This might be because sentencing typically involves both backward-looking decisions, related to the blameworthiness of the crime, as well as forward-looking decisions, about the offender’s prospective risk of recidivism. Evidence-based sentencing quantifies the predictive aspects of decision-making by incorporating an assessment of risk factors (which increase recidivism risk), protective factors (which reduce recidivism risk), criminogenic needs (impairments that, if addressed, will reduce recidivism risk), the measurement of recidivism risk, and the identification of optimal recidivism-reducing sentencing interventions. Proponents for evidence-based sentencing claim that it can allow judges to “sentence smarter” by using data to distinguish high-risk offenders (who might be imprisoned to mitigate their recidivism risk) from low-risk offenders (who might be released into the community with relatively little danger). This, proponents suggest, can reduce unnecessary incarceration, decrease costs, and enhance community safety. Critics, however, note that risk assessment typically looks beyond criminal conduct, incorporating demographic and socioeconomic variables. Even if a risk factor is facially neutral (e.g., criminal history), it might operate as a proxy for a constitutionally protected category (e.g., race). The same objectionable variables are used widely in presentence reports, but their incorporation into an actuarial risk score has greater potential to obfuscate facts and reify underlying disparities. The evidence-based sentencing literature is dynamic and rapidly evolving, but this bibliography identifies sources that might prove useful. It first outlines the theoretical foundations of traditional (non-evidence-based) sentencing, identifying resources and overviews. It then identifies sources related to decision-making and prediction, risk assessment logic, criminogenic needs, and responsivity. The bibliography then describes and defends evidence-based sentencing, and identifies works on sentencing variables and risk assessment instruments. It then relates evidence-based sentencing to big data and identifies data issues. Several works on constitutional problems are listed, the proxies problem is described, and sources on philosophical issues are described. The bibliography concludes with a description of validation research, the politics of evidence-based sentencing, and the identification of several current initiatives.

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