Still waters run deep: self-control as a moderator of dark personality traits for antisocial conduct and violent attitudes
Bibliographic record
Abstract
Although self-control is frequently comorbid with other antisocial features, some individuals who exhibit psychological risk factors for antisocial conduct nevertheless have relatively high self-control. With this complexity in mind, the current study examined self-control as a potential moderator of antisociality/criminality features and violent attitudes using a community sample of 354 adult participants from Portugal. We found significant evidence that self-control moderates the dark core of personality when predicting antisociality/criminality, but not when predicting violent attitudes. We also found self-control moderates psychopathy when predicting antisocialty/criminality, but self-control had more robust moderation effects for violent attitudes. Specifically, self-control moderated narcissism, psychopathy, and sadism. Self-control did not moderate Machiavellianism in either model. Findings corroborate the notion that self-control plays an important role in moderating some dark traits of personality that are significant predictors for antisocial/criminal behaviors.
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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 | 0.000 | 0.000 |
| 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".