Psychopathy in a noninstitutional sample: Differences in primary and secondary subtypes.
Bibliographic record
Abstract
Early theoretical conceptualizations suggest psychopathy is a heterogeneous construct whereby psychopathic individuals are found in diverse populations. The current study examined male and female psychopathy subtypes in a large sample of undergraduate students (n = 1229). Model-based cluster analysis of the Psychopathic Personality Inventory-Short Form (PPI-SF) revealed two clusters in both male and female students. In males, the primary subtype evidenced greater psychopathic personality traits (i.e., Social Potency, Fearlessness, and Impulsive Nonconformity) and lower anxiety (i.e., higher Stress Immunity), whereas the secondary subtype displayed fewer psychopathic personality traits (i.e., Machiavellian Egocentricity and Blame Externalization) and higher anxiety (i.e., lower Stress Immunity). In females, the primary subtype exhibited higher scores across all PPI-SF subscales and lower anxiety whereas the secondary subtype reported lower PPI-SF subscale scores and higher anxiety. Across a diverse array of personality, affective, and behavioral external correlates, differences between the subtypes and with nonpsychopaths emerged. Implications for psychopathy in noninstitutional populations with respect to theory, research, and gender are discussed.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".