Psychopathy in a Multiethnic World: Investigating Multiple Measures of Psychopathy in Hispanic, African American, and Caucasian Offenders
Bibliographic record
Abstract
Despite the forensic relevance of psychopathy and the overrepresentation of Hispanics in the United States' criminal justice system, these two issues remain underexplored, particularly with self-report measures of psychopathy. We investigated the criterion validity of three psychopathy measures among African Americans, Caucasians, and Hispanics in a sample of 1,742 offenders. More similarity than dissimilarity emerged across groups. The factor structures of psychopathy measures among Hispanic offenders were consistent with previous findings. Few significant differences emerged between Hispanic and Caucasian offenders, with most differences emerging between African Americans and the other ethnic groups. In such instances, the correlates of psychopathy were typically weaker for African Americans. The Psychopathy Checklist-Revised yielded fewer psychopathy × ethnicity interactions than the Psychopathic Personality Inventory and Levenson Primary and Secondary Psychopathy Scales. Overall, these psychopathy measures showed reasonable validity across these cultural groups.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".