Prolific and Priority Offenders in British Columbia, Canada: A Preliminary Analysis of Recidivism1
Notice bibliographique
Résumé
IntroductionThere is emerging consensus in correctional literature that a disproportionate amount of crime (particularly property crime) is committed by a minority of offenders (Marlow, 2007; Mawby & Worrall, 2004; Millie & Erol, 2006; Vennard & Pearce, 2004). There is also general agreement among scholars that custody alone is a relatively ineffective method of reducing offending (Moore et al., 2006), and that 'getting tough on crime' has been unsuccessful (Andrews & Bonta, 2010). These realizations have spurred a variety of programs in several countries that emphasize inter-agency collaboration as a means of improving offender outcomes and increasing community safety (Mawby & Worrall, 2004). Illustrative programs are predicated on the emerging concept of therapeutic jurisprudence (Public Safety Canada and Alberta Solicitor General, 2010) and growing evidence that successful criminal justice policy requires a focus on evidence-based offender treatment and rehabilitation practices (Andrews & Bonta, 2010).A central feature of this new approach is targeted and intensive offender surveillance, with a core component involving coordinated police and probation partnerships or polibation (see Nash, 1999). These partnerships are further supported by an integrated team of service providers that deliver interventions tailored to local priority and prolific offenders including substance use and mental health treatment, as well as referrals to employment, income assistance and housing programs. This assertive outreach is complemented by a second component of the strategy - prompt apprehension and conviction following re-offending or breaches of sentence conditions (Worrall & Mawby, 2004). Swiftresponse to re-offending is expedited by dedicated Crown Counsel who manage files generated as a result of the targeting and increased of offenders. To date, these strategies have predominantly applied toward chronic property crime offenders (Mawby & Worrall, 2004; Merrington, 2006; Vennard & Pearce, 2004).By design, these programs give rise to two quite different outcome measurements, each implying possible program success (i.e., a reduction in convictions and timely reconvictions). As a consequence, the clear selection of appropriate measures of effectiveness has important implications for research and evaluation. The majority of the available evaluations are based on initiatives in England and Wales (see Roberts, 2005). Variations of the scheme have also been evaluated in Australia, the United States and at the federal level in Canada (Pottruff, 2010). While the US has become the world leader in intensive programs (ISP) for adult offenders, it is important to note that there is no standardized ISP model (Moore et al., 2006). Few peer-reviewed outcome analyses of such programs exist.Whereas deterrence is the cornerstone of most US initiatives (which date back to the 1960s), UK projects tend to include a corresponding focus on offender treatment and rehabilitation (Moore et al., 2006). Worrall & Mawby (2004) describe three generations of intensive supervision (p.268). These began in the early 1970s with a now infamous project called IMPACT (Intensive Matched Probation and After-Care Treatment), which involved matching offenders to various types of probation interventions. Evaluations reported very unfavorable results, including higher rates of recidivism among program participants than non-participants (Worrall & Mawby, 2004). A number of similar ISPs followed in the 1980s and early 1990s. These also included a focus on surveillance and were primarily targeted at young adults between the ages of 17 and 25 (Moore et al., 2006). While these were also largely unsuccessful at reducing recidivism, evaluations did identify a number of secondary benefits associated with the projects (Worrall et al., 2003). Fast tracking of drug assessments and treatments were recognized as particularly valuable (Worrall, 2001). …
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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