Adolescents Who Have Sexually Offended
Bibliographic record
Abstract
It is unclear whether deviant sexual preferences distinguish adolescents who commit sex offenses in the same way that such deviance characterizes adult sex offenders. We compared male adolescents (mean age = 15 at the time of a referral sex offense), matched adult sex offenders, and normal men (adult nonoffenders or nonsex offenders). We hypothesized the following: phallometric responses of the adolescents would be similar to those of adult sex offenders and would differ from normals; adolescents with male child victims would exhibit greater evidence of sexual deviance than those whose only victims were female children; among adolescents who had molested children, those with a history of sexual abuse would exhibit more evidence of sexual deviance than those with no such history; and phallometric measures would predict recidivism. With some notable exceptions or qualifications, results confirmed the hypotheses. Phallometry has valid clinical and research uses with adolescent males who commit serious sex offenses.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".