The effect of boredom, psychopathy and sadism on unprovoked aggression towards others
Bibliographic record
Abstract
Purpose The authors examined whether state boredom, psychopathy, sadism and trait boredom proneness would increase the tendency to inflict physical pain on others. Previous research suggests that state boredom increases aggression in individuals with high sadistic traits. This study aims to examine whether psychopathic traits similarly interact with boredom to predict unprovoked aggression. Design/methodology/approach Participants viewed a boring (men folding laundry) or interesting (BBC Deep Sea documentary) video mood induction before playing an online game under the ruse that there was another participant in the other room. The “winner” of the game was then given the chance to blast their opponent with white noise – presumably, an unpleasant experience. Findings While boredom proneness and psychopathy were highly correlated in the sample (with a stronger relation between boredom proneness and secondary psychopathy), boredom proneness showed no relation to the intent to inflict pain on others. In fact, in moderation models, state boredom dampened the relation between primary psychopathy and aggressive actions such that those low in boredom and high in psychopathy were more likely to administer louder and longer noise blasts to their opponent. Neither state boredom nor trait boredom proneness moderated the relation between sadism and aggression strength. The authors interpret these counterintuitive findings in the context of models of boredom and psychopathy. Research limitations/implications As the sample was conducted on a university population, there may be limited generalizability for individuals with clinical levels of psychopathy. Originality/value This paper examines the link between boredom and aggressive behaviour in those with psychopathic traits, a relation that has not previously been examined in depth.
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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) | 0.000 | 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".