Mentorship: A Missing Piece to Manage Juvenile Intensive Supervision Programs and Youth Gangs?
Bibliographic record
Abstract
Intensive supervision probation (ISP) has proven generally ineffective for youth. In this article we argue that mentorship, an intervention with increasing empirical support in the literature, is a missing treatment component. We test this proposition with results from the Spotlight Serious Offender Services Unit, an urban-based Canadian ISP program that targets high-risk gang youth. Unique to Spotlight is their adoption of street mentors to work with youth in the community. Our study incorporated quantitative and qualitative approaches: client interviews and researcher observation of street mentors coupled with comparison of recidivism outcomes between a comparison group (N = 85) of high-risk young offenders and Spotlight (N = 57) clients, matched via a propensity score matching (PSM) procedure. Spotlight cases did significantly better than the comparison group on all recidivism outcomes examined. Qualitative interview and observation data supported mentorship efficacy. Given the lack of effectiveness of other ISPs observed in the literature, we argue that mentorship makes a difference.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".