Correctional interventions for women offenders: a rapid evidence assessment
Bibliographic record
Abstract
Purpose – A Rapid Evidence Assessment (REA) determined the effectiveness of correctional programmes for women offenders and examined features of programmes providing the strongest outcomes. The paper aims to discuss these issues. Design/methodology/approach – Electronic databases and web sites were reviewed to identify literature focused on interventions with female offenders published since 2006, the end point of the last REA conducted in the area. The following retention criteria were applied: participants were over age 18; sample included women and results are reported separately for women; study included an appropriate comparison group; study included recidivism as an outcome measure. Studies’ methodological design quality was assessed using the Maryland Scientific Methods Scale. Findings – In total, one meta-analysis and 22 studies reflecting 17 unique samples, published from 2006 to December 2014, were identified. Overall, the best evidence suggests that the following programmes and approaches have an evidence base: first, substance abuse treatment, in particular in-custody or hierarchical therapeutic community programmes; second, gender-responsive programmes that emphasize existing strengths and competencies, as well as skills acquisition; and third, following in-custody programme treatment with participation in community follow-up sessions. There is also promising evidence for the use of community opioid maintenance among heroin addicted women. Originality/value – This review demonstrated that since 2006 the number of high-quality research studies assessing women’s correctional outcomes has grown considerably. The results provide guidance to programme designers and administrators on programmes for women offenders likely to be effective in promoting public safety goals and offender reintegration.
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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 | 0.092 | 0.211 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.012 |
| Bibliometrics | 0.018 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".