Effectiveness of Correctional Programs With Ethnically Diverse Offenders
Bibliographic record
Abstract
Numerous studies have examined the effects of cognitive-behavioural therapy (CBT) on criminal recidivism, and several meta-analyses have confirmed the overall effectiveness of this approach. Few studies, however, have examined the efficacy of these programs specifically with adult offenders from diverse ethnic backgrounds. The present research uses meta-analytic techniques to examine the outcomes for Canadian federal offenders participating in correctional programs according to self-identified ethnic group (Caucasian, Aboriginal, Black, and Other). Correctional programs within the Correctional Service of Canada adhere to the Risk, Need, Responsivity principles outlined in the effective correctional literature. Within-group analyses compared offenders from the same ethnic background who participated in correctional programs with a nontreatment comparison group. Odds ratios ranged from 1.36 to 1.76, indicating significant reductions in recidivism for offenders participating in correctional programs, regardless of ethnic status. Furthermore, the difference in effect size magnitude between ethnic groups was nonsignificant suggesting offenders from a wide variety of ethnic backgrounds can benefit from correctional programs rigorously developed and implemented using a CBT framework.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".