Effects of automating recidivism risk assessment on reliability, predictive validity, and return on investment (ROI)
The relationship between reliability and validity is an important but often overlooked topic of research on risk assessment tools in the criminal justice system. By using data from the Minnesota Screening Tool Assessing Recidivism Risk (MnSTARR), a risk assessment instrument the Minnesota Department...
Authors: | ; |
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Format: | Electronic Article |
Language: | English |
Published: |
2017
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In: |
Criminology & public policy
Year: 2017, Volume: 16, Issue: 1, Pages: 235-269 |
Online Access: |
Volltext (Verlag) |
Journals Online & Print: | |
Check availability: | HBZ Gateway |
Keywords: |
Summary: | The relationship between reliability and validity is an important but often overlooked topic of research on risk assessment tools in the criminal justice system. By using data from the Minnesota Screening Tool Assessing Recidivism Risk (MnSTARR), a risk assessment instrument the Minnesota Department of Corrections (MnDOC) developed and began using in 2013, we evaluated the impact of inter‐rater reliability (IRR) on predictive performance (validity) among offenders released in 2014. After comparing the reliability of a manual scoring process with an automated one, we found the MnSTARR was scored with a high degree of consistency by MnDOC staff as intraclass correlation (ICC) values ranged from 0.81 to 0.94. But despite this level of IRR, we still observed a degradation in predictive validity given that automated assessments significantly outperformed those that had been scored manually. Additional analyses revealed that the more inter‐rater disagreement increased, the more predictive performance decreased. The results from our cost–benefit analyses, which examined the anticipated impact of the MnDOC's efforts to automate the MnSTARR, showed that for every dollar to be spent on automation, the estimated return will be at least $4.35 within the first year and as much as $21.74 after the fifth year. |
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ISSN: | 1745-9133 |
DOI: | 10.1111/1745-9133.12270 |