Are Psychopathic Traits Associated with Core Social Networks? An Exploratory Study in University Students
Bibliographic record
Abstract
In a sample of 480 university students, we examined associations between self-ratings of psychopathic traits, made using the Comprehensive Assessment of Psychopathic Personality (CAPP), the Psychopathic Personality Inventory: Short Form (PPI: SF), and self-ratings of the structure of their core social networks (i.e., best friends, intimates). Results indicated that higher self-ratings of domains (CAPP) and subscales (PPI: SF) related to interpersonal dominance, manipulation, poor attachment, and emotional regulation were associated with less connected core networks. We interpret the dominance and manipulation domain and subscale findings as preliminary evidence of a deliberate strategy to provide a more influential position within one’s social network. As for the associations with the attachment and emotional regulation domain and subscale findings, we suggest this could be reflective of deficits or a lack of desire both in establishing and maintaining long-term relationships.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".