Promoting disengagement: Effects of a gang intervention and exiting Program on negative police contacts
Why this work is in the frame
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Bibliographic record
Abstract
To address gang involvement in British Columbia, Canada, the Gang Intervention and Exiting Program (GIEP) was developed to assist individuals in leaving the gang lifestyle. The GIEP uses an individualized case management approach including external service referrals and is delivered by police officers and civilian case managers. The current study examines GIEP impacts on total negative police reports, as well as violent, weapons, and drug trafficking/production offences. Outcomes were assessed using a single group repeated measures design on the population of clients served from program inception (November 2016) to December 2021 ( n = 155). Population-averaged generalized estimating equations (GEEs) were implemented to examine the change in total negative police reports and violent, drug, and weapons offence count over time. Longitudinal analyses found significantly fewer police reports 12-, 18-, 30-, and 36-months post-entry when compared to the 6-month period preceding program entry. Findings also suggest a decrease in violent offending at 24-and 36-months post-entry, as well as in drug trafficking/production offences at 12-, 18-, and 30-months post-entry. No impact was found for weapons offences. Overall findings suggest that an individualized approach to providing services and supports can be effective for reducing negative police contacts and criminality among gang-involved individuals. • The Gang Intervention and Exiting Program reduced negative police contacts. • Males had a significant reduction in police contacts, while females did not. • The intervention resulted in a significant reduction in violent and drug offences. • An individualized exiting approach can be effective for reducing gang involvement. • Gang exiting interventions combining police and civilians are a promising approach.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it