The Influence of Psychosocial Maturity on Adolescent Offenders' Delinquent Behavior
Bibliographic record
Abstract
Prior research has demonstrated the predictive utility of psychosocial maturity in understanding adolescents' decison making regarding antisocial behaviors and other legal decisions. This study investigated the influence of psychosocial maturity on adolescent offenders' self-report of delinquent behaviors over a 12-month time period. A total sample of 136 male and female juvenile offenders were recruited from two juvenile justice settings. Consistent with prior research, results indicated significant correlations between psychosocial maturity variables and self-reported delinquent behavior with the current results revealing a moderating effect of gender on these associations. Separate regression analyses were conducted for male and female juvenile offenders. After controlling for age and setting, the psychosocial maturity variable of temperance consistently predicted self-reported total, violent, and nonviolent delinquency for boys.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".