To Reoffend or Not to Reoffend? An Investigation of Recidivism Among Individuals With Sexual Offense Histories and Psychopathy
Bibliographic record
Abstract
Although psychopathy is a well-established risk factor for recidivism among those who have committed sexual offenses, there are nonetheless some individuals with sexual offense histories who are high in psychopathy but do not recidivate. This population-nonrecidivating psychopathic sex offenders (NRP-SOs)-was the focus of the current investigation. Data from 111 individuals with sexual offense histories who received a Hare Psychopathy Checklist-Revised (PCL-R) rating of at least 25 (suggesting the presence of psychopathy) were analyzed. With recidivism operationalized as the accrual of any new serious-that is, violent or sexual-charges, 39 recidivated (RP-SOs), whereas 72 did not (NRP-SOs). A logistic regression was conducted to assess whether NRP-SOs could be differentiated from RP-SOs. Being older at the time of release, a lesser criminal history, and being married predicted nonrecidivism. PCL-R factor scores and sexual deviance were not predictive. These findings highlight the heterogeneity that exists, even among those high in psychopathy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".