Clinical Override Use With the Youth Level of Service/Case Management Inventory: Predictive Validity and Factors Associated With Case Management Use
Bibliographic record
Abstract
Clinical discretion by youth probation officers to override the actuarial risk assessment classification on the Youth Level of Service/Case Management Inventory (YLS/CMI) is an important feature of case management practices. In a sample of 1,259 youth, the impact of clinical override on the predictive validity of the YLS/CMI and factors associated with override use were studied. Using receiver operating characteristic (ROC) analyses, the YLS/CMI demonstrated large effect size predictive validity values for general recidivism. Override occurred with 10.8% of youth and was more likely to be used with younger youth who had a sexual or violent index offense or those at the upper end of the moderate risk level. For youth where override was used, the YLS/CMI predictive validity became non-significant and fell to chance levels. The implications of these findings for field case management use, training, and probation officer decision-making practices are highlighted.
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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 | 0.004 | 0.025 |
| 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 | 0.001 |
| 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".