Prolific and Priority Offenders in British Columbia, Canada: A Preliminary Analysis of Recidivism1
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".