Cross-National Differences in the Assessment of Psychopathy: Do They Reflect Variations in Raters' Perceptions of Symptoms?
Bibliographic record
Abstract
Cross-national differences in the prevalence of psychopathy have been reported. This study examined whether rater effects could account for these differences. Psychopathy was assessed with the Psychopathy Checklist-Revised (PCL-R; R. D. Hare, 1991). Videotapes of 6 Scottish prisoners and 6 Canadian prisoners were rated by 10 Scottish and 10 Canadian raters. No significant main or interaction effects involving the nationality of raters were detected at the level of full scores or factor scores. Using a generalizability theory approach, it was demonstrated that the interrater reliability of total scores was good, that is, the proportion of variance in test scores attributable to raters was small. The interrater reliability of factor scores was lower, typically falling in the fair range. Overall, the results suggest that the reported cross-national differences are more likely to be in the expression of the disorder rather than in the eye of the beholder.
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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 | 0.051 | 0.118 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".