Risk Assessment in Juvenile and Young Adult Offenders: Predictive Validity of the SAVRY and SAPROF-YV
Bibliographic record
Abstract
Most juvenile risk assessment tools heavily rely on a risk-focused approach. Less attention has been devoted to protective factors. This study examines the predictive validity of protective factors in addition to risk factors, and developmental differences in psychometric properties of juvenile risk assessment. For a national Dutch sample of 354 juvenile and young adult offenders (16-26 years) risk and protective factors were retrospectively assessed at discharge from seven juvenile justice institutions, using the Structured Assessment of Violence Risk in Youth (SAVRY) and Structured Assessment of Protective Factors for violence risk - Youth Version (SAPROF-YV). Results show moderate validity for both tools predicting general, violent, and nonviolent offending at different follow-up times. The SAPROF-YV provided incremental predictive validity over the SAVRY, and predictive validity was stronger for younger offenders. Evidently both the SAVRY and SAPROF-YV seem valid tools for the assessment of recidivism risk in juvenile and young adult offenders. Results highlight the importance of protective factors, especially in juvenile offenders, emphasizing the need for a balanced risk assessment.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".