Dark or disturbed?: Predicting aggression from the Dark Tetrad and schizotypy
Bibliographic record
Abstract
Research on the personality foundations of aggression typically implicates either (a) aspects of the so-called "Dark Tetrad" or (b) severe mental disturbance (psychosis). The appearance of psychotic symptoms in general populations is termed schizotypy. We conducted two studies to compare the effects of dark personalities and schizotypy on aggression. Study 1 used standard inventories to investigate the overlap of Dark Tetrad traits with schizotypy in a sample of 977 undergraduates. All tetrad traits except narcissism were positively associated with schizotypy, but only at moderate levels. Study 2 administered the same personality battery to 303 members of an online community sample: Aggression outcomes were measured with both self-reports and a behavioral measure-the Voodoo Doll Task. Regression analyses determined the unique contributions of the five personality variables. Two dark traits-psychopathy and sadism-were strong predictors of self-report aggression. Schizotypy added incrementally to the Dark Tetrad in predicting both self-report and behaviorally measured aggression.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".