Revisiting prediction models in policing: Identifying high-risk offenders
The use of prediction models for classifying offenders has been a common practice by the criminal justice system. Given the recent developments in criminal career research and continuing evidence that a small proportion of chronic offenders are responsible for the majority of crime, there is a conti...
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| Format: | Electronic Article |
| Language: | English |
| Published: |
2006
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| In: |
American journal of criminal justice
Year: 2006, Volume: 31, Issue: 1, Pages: 35-50 |
| Online Access: |
Volltext (lizenzpflichtig) Volltext (lizenzpflichtig) |
| Check availability: | HBZ Gateway |
| Keywords: |
| Summary: | The use of prediction models for classifying offenders has been a common practice by the criminal justice system. Given the recent developments in criminal career research and continuing evidence that a small proportion of chronic offenders are responsible for the majority of crime, there is a continued need to identify high-risk offenders early on in their offending careers. The present study provides support for the accuracy of an innovative prediction instrument that was developed for identifying high-risk offenders in a rural county in a southern state. Offender risk classification was found to be associated with reoffending across different dimensions of assessment and the high-risk offenders had accumulated a greater mean number of arrests upon six-month follow-up when compared to the medium and low-risk offenders. Policy implications and directions for future research incorporating prediction models in policing are also discussed. |
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| ISSN: | 1936-1351 |
| DOI: | 10.1007/BF02885683 |
