The Effectiveness of the Tupiq Program for Inuit Sex Offenders
Bibliographic record
Abstract
This study examines the effectiveness of the Tupiq program, a culturally specific program for Inuit sex offenders that incorporates cognitive behavioural methods with traditional Inuit knowledge and culture led by Inuit healers and facilitators. Outcomes of 61 offenders who participated in the Tupiq program and were released were compared with outcomes of a cohort of 114 released Inuit sex offenders incarcerated during the same time period who had taken alternative sex offender treatment programs, or had not attended any sex offender program. On release, Tupiq participants had significantly lower rates of general reoffending and violent reoffending than those in the combined comparison group. The hazard of reoffending for the comparison group was almost twice that of the Tupiq group. Although the sexual reoffending rate for the Tupiq participants was less than half of that of the comparison group, the difference between the two groups was not significant because of reduced statistical power. Survival analysis controlling for covariates confirmed significantly lower rates of general reoffending for the Tupiq group. Further analyses comparing the outcomes of the subgroup of offenders in the comparison group who participated in alternative sex offender treatment programs with those who participated in Tupiq indicated that Tupiq participants had significantly lower rates of both general and sexual reoffending. These positive results for this culturally specific program suggest that similarly designed interventions have a probability of contributing to the reduction of sexual offending within Inuit communities and, potentially, other jurisdictions that work with cultural minority sex offender groups from relatively isolated communities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".