The effects of positive peer culture on the recidivism rates of male young offenders in Manitoba
Bibliographic record
Abstract
The study analysed a sample of male youth correctional discharges within Manitoba from January 1, 2000 to December 31, 2000. Agassiz Youth Centre (AYC) discharges were compared to a matched sample of discharges from other institutions using archival data (N = 150). Subsequent numbers of charges, convictions, months incarcerated and times incarcerated from each group were examined over two years in order to assess the effectiveness of AYC's Positive Peer Culture (PPC) program. These variables were compared while controlling for age, race, education, place of residence, family background, gang affiliation, type of offence, seriousness of most serious offence, number of times incarcerated, past risk of suicide, and risk to reoffend. Results suggest that PPC does have a significant impact on certain measures of recidivism including total number of times incarcerated, total number of months incarcerated, seriousness of the most serious offence and time before reinvolvement. Exploratory analysis also measured PPC's comparative effect on offenders with different personal characteristics. Results suggest that youth who live in rural areas, who do not have a history of suicide risk, who reside with at least one parent, or who are a low risk to reoffend had better outcomes if they were discharges from AYC than from the comparison group. Although this study is unable to isolate all confounding variables, it will be able to give some insight into the effect of PPC on recidivism. Recommendations address the application and interpretation of PPC at AYC as well as the direction for future research. An extensive literature review is also included.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".