It’s what’s inside that counts: how dark triad traits mediate gender differences in prosocial behavior
Bibliographic record
Abstract
BACKGROUND: This study examined whether gender differences in empathy and prosocial behavior operate through Dark Triad personality traits. By treating personality as the mediator, we move beyond male–female comparisons and provide a clear, culturally relevant explanation for when and why gender-linked helping patterns emerge. METHODS: Using convenience sampling, 323 Chinese undergraduates (133 males, 190 females) completed validated self-report questionnaires: the Questionnaire of Cognitive and Affective Empathy (QCAE), the Prosocial Tendencies Measure (PTM), and the Dirty Dozen (DD). Mediation and sequential mediation analyses were conducted using SPSS and Mplus. RESULTS: Empathy did not differ by gender. However, psychopathy significantly mediated the link between gender and both empathy dimensions. Machiavellianism and psychopathy mediated gender differences in anonymous and compliant prosocial behaviors. A sequential pathway showed that psychopathy reduced affective empathy, which in turn lowered altruistic behavior among men. CONCLUSIONS: Gender showed little direct association with empathy and prosocial behavior once Dark Triad traits were accounted for; psychopathy (and, for some domains, Machiavellianism) mediated the observed differences. These findings suggest that research on prosociality should prioritize underlying personality mechanisms rather than gender per se.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".