Evaluation of an Innovative Post-Arrest Diversion Program: 12-Month Recidivism Analysis
Bibliographic record
Abstract
We report the results of an evaluation study of a diversion program, operated by the Miami-Dade County Juvenile Assessment Center in Florida. The Post-Arrest Diversion (PAD) program represents an innovative approach to treatment and intervention within the juvenile justice system that utilizes standardized psychosocial risks and needs assessment to provide individual treatment for first-time, non-violent juvenile offenders. The present study evaluated the effectiveness of the PAD program with regard to one-year follow-up recidivism. The sample is comprised of 409 youths (255 male; 154 female) who entered PAD between April and June of 2003. Stepwise, Poisson and OLS regression analyses of the effects of socio-demographic characteristics, type of charges leading to program involvement, recidivism risk level, PAD completion, and arrests while in PAD on the number of recidivism arrests and charges were conducted. The findings suggest that successful completion of PAD significantly reduces recidivism.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".