Smart Decarceration: Is It Possible to Detain Fewer People and Reduce Arrests?
This paper provides the results of a thought experiment to see what would have happened if a jurisdiction made release decisions solely based on risk assessment predictions of new arrests. Random forest imputation is used with data from all admissions to a large county jail system (n = 28,188) to fo...
| Publicado en: | Crime & Delinquency Vol. 72; no. 1; pp. 3 - 34 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Sage Publications Inc.
Jan2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=190434552&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 190434552 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00111287 CRD jtl: Crime & Delinquency issn: 00111287 maglogo: Y pubinfo: dt: Jan2026 vid: 72 iid: 1 pid: 344 pub: Sage Publications Inc. artinfo: ui: 190434552 10.1177/00111287241301017 ppf: 3 ppct: 31 formats: tig: atl: Smart Decarceration: Is It Possible to Detain Fewer People and Reduce Arrests? aug: au: DeMichele, Matthew Silver, Ian A. Labrecque, Ryan M. affil: RTI International, Research Triangle Park, NC, USA su: Arrest Prisoners Jails Legal judgments Risk assessment Random forest algorithms Criminal law reform sug: subj: Arrest Prisoners Jails Legal judgments Commercial and Institutional Building Construction Provincial correctional services Municipal correctional services Correctional Institutions Risk assessment Random forest algorithms Criminal law reform keyword: decision making jail incarceration pretrial detention simulations decision making jail incarceration pretrial detention simulations ab: This paper provides the results of a thought experiment to see what would have happened if a jurisdiction made release decisions solely based on risk assessment predictions of new arrests. Random forest imputation is used with data from all admissions to a large county jail system (n = 28,188) to forecast new arrests for individuals detained by the court. After imputing outcome rates for the detained, we rank order everyone by their predicted probability of future arrest from lowest to highest probability and compare release and new arrest rates between the predicted outcomes and observed release decisions. The results show the risk-based release approach has the potential to reduce the detained population by 7% and reduce new arrests by 13% compared to current practices. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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