Cluster analysis of Primary and Secondary Psychopathy in the General Population
Bibliographic record
Abstract
Abstract People with high levels of psychopathy cause damage to interpersonal relationships, being also found in the general community. Therefore, it is necessary to explore how this trait manifests in the general community. Thus, the objective was to study the subtypes of psychopathy (primary and secondary) in the general community and their association with personality (i.e., HEXACO). Participants were 116 people aged between 18 and 69 years (78.3% women). Results indicated four groups: high psychopathy, low psychopathy, high primary psychopathy, and high secondary psychopathy. Honesty-Humility factor was the one that best discriminated among the subtypes. We concluded that different personality traits are related to the subtypes of psychopathy, which can impact the assessment and intervention process of people with higher levels in this construct.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".