Convergent and Predictive Validity of the Jesness Inventory in a Sample of Juvenile Offenders
Bibliographic record
Abstract
The present study examined the convergent and predictive validity of the Jesness Inventories (JI) in a sample of 138 juvenile offenders, completed in the course of routine service delivery. JI profiles were compared with ratings on three standardized forensic clinical scales: the Youth Level of Service/Case Management Inventory, Psychopathy Checklist: Youth Version, and Violence Risk Scale-Youth Version. The JI Asocial Index and the Undersocialized Active and Group-Oriented Conformist Interpersonal Maturity Level (I-level) subtypes demonstrated the strongest pattern of convergence and most consistently predicted recidivism. The Asocial Index did not incrementally predict recidivism after controlling for scores on the standardized forensic clinical scales; however, meaningful differences among broad I-Level groups (I-3 and I-4) remained after controlling for risk. Risk-need-responsivity applications of the JI (i.e., in terms of treatment dosage, identifying treatment targets, and adaptation of services) are discussed within the context of a comprehensive forensic assessment framework to inform case formulation, service delivery, and decision making with justice involved youth.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".