Does psychopathy predict institutional misconduct among adults? A meta-analytic investigation.
Bibliographic record
Abstract
Narrative reviews have raised several questions regarding the predictive validity of the Hare Psychopathy Checklist-Revised (PCL-R; R. D. Hare, 2003) and related scales in institutional settings. In this meta-analysis, the authors coded 273 effect sizes to investigate the association between the Hare scales and a hierarchy of increasingly specific forms of institutional misconduct. Effect sizes for Total, Factor 1, and Factor 2 scores were quite heterogeneous overall and weakest for physically violent misconduct (r-sub(w) = .17, .14, and .15, respectively). Moderator analyses suggested that physical violence effect sizes were smaller in U.S. prison samples (r-sub(w) = .11) than in non-U.S. prison samples (r-sub(w) = .23). Findings are discussed in terms of the utility of the Hare measures for decision-making in institutional and other contexts.
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.014 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".