Rehabilitation group coparticipants’ risk levels are associated with offenders’ treatment performance, treatment change, and recidivism.
Bibliographic record
Abstract
OBJECTIVE: Exposure to antisocial others within treatment group sessions may have negative impact. We extend prior research with adolescents by examining rehabilitation group composition among adult male incarcerated offenders. METHOD: Data were gathered from institution files of rehabilitation completers (N = 1,832; M age = 33.5; 19% Aboriginal, 68% Caucasian), including general, substance, violent, and sex offenders. Capacities for treatment (including motivation, learning ability, and inhibitory control) were gathered from intake assessments. At the beginning and end of rehabilitation, providers rated program performance. Risk for recidivism and postrelease recidivism were gathered from official files, up to 3 years following release. RESULTS: Group effects accounted for up to 40% of variance in program outcomes. Group features (average group participant risk to reoffend and risk score diversity) significantly interacted with treatment capacities to explain program outcomes. Most models revealed a dampening effect whereby the positive association between capacities and outcome was reduced in groups of higher risk and more risk diverse coparticipants. Group composition typically accounted for 30-38% of variance between groups, but total variance in outcome explained was generally small. Higher average group risk predicted postrelease recidivism among family violence offenders. CONCLUSIONS: Coparticipants should be considered when researching and providing group programs to adult offenders, with specific attention toward how positive outcomes may be attenuated in the presence of criminogenic coparticipants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".