Criterion Validity of the Psychopathy Checklist in Legal Contexts: An Updated Meta-Analysis
Bibliographic record
Abstract
The Psychopathy Checklist (PCL) scales are the most widely used instruments in the assessment of psychopathic personality traits. This updated meta-analysis represents the most extensive synthesis of the PCL scales' criterion validity regarding recidivism and institutional outcomes in legal contexts. According to the results, the PCL total score and Factor 2 criterion validity were moderate and significantly higher for Factor 2 than the total score. The criterion validity of Factor 1 was small and significantly lower than Factor 2 and the total score. The criterion validity of the PCL total score varied considerably between outcomes, with moderate effect sizes for general and violent recidivism, institutional misconduct and violence, and small effect sizes for sexual and intimate partner violence recidivism. A moderator analysis indicated country and sex as the only significant predictors moderating the PCL scales' criterion validity. The total score and Factor 2 were less predictive in the United States than in Canada and Europe for institutional violence. Factor 1 was more predictive in females than males for general and violent recidivism. The present findings may support decision-makers in interpreting the prognostic value and limitations of the PCL scales in the criminal justice system. .
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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 | 0.022 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.020 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".