Correlates of Recidivism Among Adolescents Who Have Sexually Offended
Bibliographic record
Abstract
The present study investigates the recidivism rates of a sample of 351 male adolescents who sexually offended, and were assessed at an outpatient psychiatric clinic in Montreal, Canada, between 1992 and 2002. The mean age of the participants was 15.8 years (SD=1.8). Data on adolescent and adult recidivism were collected in Summer 2005 from official criminality sources in Canada. Over an 8-year follow-up period, 45% (n=158) of the participants were charged with a new criminal offense, 30% (n=104) were charged with a violent offense, and 10% (n=36) were charged with a sexual offense. Cox regression results suggest that overall, violent, and sexual recidivism can be predicted by a variety of developmental, social, and criminological factors. Paternal abandonment, childhood sexual victimization, association with significantly younger children, and having victimized a stranger were associated with a higher risk of sexual recidivism. Previous delinquency, attention deficit disorder, and childhood sexual victimization were found to increase the risk for both violent and overall recidivism. Also, the use of violence during a sex crime and victimizing a stranger were associated with violent recidivism, and school delay and association with delinquent peers were predictive of overall recidivism. The results confirm that a significant proportion of adolescents who have sexually offended pursue a criminal activity beyond adolescence, although few specialize in sexual offending.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".