The structural and predictive properties of the Psychopathy Checklist–Revised in Canadian Aboriginal and non-Aboriginal offenders.
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Bibliographic record
Abstract
We examined the structural and predictive properties of the Psychopathy Checklist-Revised (PCL-R) in large samples of Canadian male Aboriginal and non-Aboriginal offenders. The PCL-R ratings were part of a risk assessment for criminal recidivism, with a mean follow-up of 26 months postrelease. Using multigroup confirmatory factor analysis, we were able to show that the PCL-R items were invariant across these 2 groups and that a 4-factor model fit the data well. Predictive accuracy analyses (receiver operator characteristic curves and Cohen's d) generated effect sizes that were medium in magnitude overall for the PCL-R total score in the prediction of violent, nonviolent, and general criminal recidivism (area under the curve=.63-.70, Cohen's d=.28-.42) for both ancestral groups. When disaggregated into its constituent factors, for both ancestral groups, the Lifestyle and Antisocial factors consistently and significantly predicted all recidivism outcomes, whereas the Interpersonal and Affective factors did not significantly predict any of the recidivism outcomes. Finally, structural equation modeling results with the total sample indicated that the PCL-R factors were able to account for 32% of the variance in a latent recidivism factor. Implications regarding the latent structure of psychopathy and the clinical use of the instrument with Aboriginal and non-Aboriginal male offenders are discussed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it