Effects of juvenile court exposure on crime in young adulthood
Bibliographic record
Abstract
BACKGROUND: The juvenile justice system's interventions are expected to help reduce recidivism. However, previous studies suggest that official processing in juvenile court fails to reduce adolescents' criminal behavior in the following year. Longer term effects have not yet been investigated with a rigorous method. This study used propensity score matching to assess the impact of juvenile court processing into young adulthood. METHOD: Participants were part of a prospective longitudinal study of 1,037 boys from low- socioeconomic areas of Montreal, followed from ages 6-25 years. During their adolescence, 176 participants were processed in juvenile court, whereas 225 were arrested, but not sent to court. Propensity score matching was used to balance the group of participants exposed to juvenile court and the unexposed comparison group on 14 preadolescent child, family and peer characteristics. The two groups were compared on their official adult criminal outcomes. RESULTS: The risk of conviction for an adult offence was 50.0% for court-processed participants compared with 24.3% for their matched counterparts, OR = 3.13, 95% CI = 1.80-5.44. Court-processed participants committed an average of 0.39 violent crimes, compared with 0.15 for their matched counterparts; Poisson model IRR = 2.60, 95% CI = 1.39-4.87. They also committed an average of 2.38 nonviolent crimes, compared to 1.30 for their matched counterparts, IRR = 1.87, 95% CI = 1.19-2.93. CONCLUSIONS: Rather than decreasing recidivism, juvenile court intervention increased both violent and nonviolent future crimes. Along with previous studies, this study highlights a pressing need for more research and knowledge transfer about effective interventions to reduce recidivism among youths who commit crime.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".