Reducing Violence Risk? Some Positive Recidivism Outcomes for Canadian Treated High-Risk Offenders
Bibliographic record
Abstract
In pursuit of “what works” in violent offending behavior programs, there remain insufficient evaluations of program outcomes. Three hundred forty-five offenders from the Canadian Violence Prevention Program (VPP) were compared after an average 3-year follow-up with 338 non-VPP participants. Outcomes measured were new convictions for violent, sexual, or general offenses. Intent-to-treat design was used. Subsequently, participants who completed or did not complete the program were compared with the non-VPP group. Further analyses considered Indigenous and non-Indigenous subgroups. Overall, lower recidivism rates were associated with VPP completion, both in the complete sample and ethnic subgroups. However, the main finding of significantly lower likelihood of violent recidivism was found only for the Indigenous offenders, while significantly lower likelihood of general (nonviolent) recidivism was specific to non-Indigenous offenders. Results are interpreted cautiously in relation to program effectiveness given the quasi-experimental design and the important implications of outcome studies for correctional services.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".