Assessment of Reoffense Risk in Adolescents Who Have Committed Sexual Offenses
Bibliographic record
Abstract
Clinicians are often asked to assess the likelihood that an adolescent who has committed a sexual offense will reoffend. However, there is limited research on the predictive validity of available assessment tools. To help address this gap, this study examined the ability of the Estimate of Risk of Adolescent Sexual Offense Recidivism (ERASOR), the Youth Level of Service/Case Management Inventory (YLS/CMI), the Psychopathy Checklist: Youth Version (PCL:YV), and the Static-99 to predict reoffending in a sample of 193 adolescents. Youth were followed for an average of 7.24 years after discharge from a residential sex offender treatment program. Although none of the instruments significantly predicted detected cases of sexual reoffending, ERASOR’s structured professional judgments nearly reached significance ( p = .069). Both the YLS/CMI and the PCL:YV predicted nonsexual violence, any violence, and any offending; however, the YLS/CMI demonstrated incremental validity over the PCL:YV. Although the Static-99 has considerable support with adult sex offenders, it did not predict sexual or general reoffending in the present sample of adolescents.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".