Risk Assessment With Young Offenders
Bibliographic record
Abstract
The current investigation is a meta-analysis of the predictive accuracy of three well-known forensic instruments used to appraise risk with young offenders: youth adaptations of the Level of Service Inventory and Psychopathy Checklist and the Structured Assessment of Violence Risk for Youth. Through several avenues, 49 potentially suitable published and unpublished studies (across 44 samples representing 8,746 youth) were identified and evaluated for inclusion. Predictive accuracy for general, nonviolent, violent, and sexual recidivism was examined for the three sets of measures. Mean weighted correlations for each of the three measures were significant in the prediction of general, nonviolent, and violent recidivism, with no single instrument demonstrating superior prediction. Separate analyses of specific young offender groups further supported the predictive accuracy of youth adaptations of the Level of Service Inventory among male, female, Aboriginal, and non-Aboriginal youth. Implications regarding the utility of young offender risk measures for enhancing clinical service provision with youth clientele are discussed.
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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 | 0.031 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.010 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".