Predictive Validity of Risk Assessments in Juvenile Offenders
Bibliographic record
Abstract
This study examined the validity and reliability of the Structured Assessment of Violence Risk in Youth (SAVRY), the Youth Level of Service/Case Management Inventory (YLS/CMI), and the Psychopathy Checklist: Youth Version (PCL:YV) in a sample of Spanish adolescents with a community sanction (N = 105). Self-reported delinquency with a follow-up period of 1 year was used as the outcome measure. The predictive validity of the three measures was compared with the unstructured judgment of the juvenile's probation officer and the self-appraisal of the juvenile. The three measures showed moderate effect sizes, ranging from area under the curve (AUC) = .75 (SAVRY) to AUC = .72 (PCL:YV), in predicting juvenile reoffending. The two unstructured judgments had no significant predictive validity whereas the SAVRY had significantly higher predictive validity compared with both unstructured judgments. Finally, SAVRY protective factor total scores and SAVRY summary risk ratings did not add incremental validity over SAVRY risk total scores. The high base rates of both violent (65.4%) and general reoffending (81.9%) underline the need for further risk assessment and management research with this population.
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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 | 0.005 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".