Intersection between Justice-Involved Youth Personality Profiles and Criminal Risk-Need Patterns
Bibliographic record
Abstract
To purpose of the current study was to inform system level decision-making about the value of integrating clinically relevant personality information with criminogenic need risk appraisal in justice-involved youth. Using a Canadian sample of youth referred for court-ordered psychological assessments ( N = 201, M age =15.62 years; 70% male), we examined the patterns of association and differentiation between youths’ Youth Level of Service/Case Management Inventory (YLS/CMI) criminogenic need/risk profiles with personality profiles derived from the personality scales of the Millon Adolescent Clinical Inventory (MACI, Millon, Millon adolescent clinical inventory. National Computer Systems, 1993). Specifically, latent profile analysis identified four MACI based personality profiles: externalizing, internalizing, dependent/followers, and complex dysregulated personality profiles. These groups varied significantly on YLS/CMI risk-need profiles. Although both externalizing and complex dysregulated sub-types represented higher criminal risk, their intervention needs diverged meaningfully. These results provide insight into the heterogeneity of justice-involved youth and point to the need for system resources that allow for appropriate intervention matching to maximize the goal of recidivism risk reduction in 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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".