Personality-Based Typology of Adolescent Male Sexual Offenders: Differences in Recidivism Rates, Victim-Selection Characteristics, and Personal Victimization Histories
Bibliographic record
Abstract
California Psychological Inventory scores from 112 adolescent male sexual offenders aged 12-19 (M = 15.59, SD = 1.46) were examined. A cluster analysis of factor-derived scores revealed four personality-based subgroups: Antisocial/Impulsive, Unusual/Isolated, Overcontrolled/Reserved, and Confident/Aggressive. Significant differences were observed between groups regarding history of physical abuse, parental marital status, residence of the offenders, and whether or not offenders received criminal charges for their index sexual assaults. Subgroup membership was unrelated to victim age, victim gender, and offenders' history of sexual victimization. Recidivism data (criminal charges) were collected for a period ranging from 2 to 10 years (M = 6.23, SD = 2.02). Offenders in the two more pathological groups (Antisocial/Impulsive and Unusual/Isolated) were most likely to be charged with a subsequent violent (sexual or nonsexual) or nonviolent offense. The four-group typology based solely on personality functioning is remarkably similar to that found by W. R. Smith, C. Monastersky, and R. M. Deisher in 1987 from their cluster analysis of MMPI scores. In addition to implications for risk prediction, the present typology is suggestive of differential etiological pathways and treatment needs.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.000 |
| 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".