Cold-Blooded and on Purpose: A Review of the Biology of Proactive Aggression
Bibliographic record
Abstract
Proactive aggression (PA) is a planned and unprovoked form of aggression that is most often enacted for personal gain or in anticipation of a reward. Frequently described as "cold-blooded" or goal oriented, PA is thought to be associated with low autonomic arousal. With this view in mind, we performed a scoping review of the biological correlates of PA and identified 74 relevant articles. Physiological findings indicated a robust association between PA and reduced resting heart rate, and to a lesser extent a relationship between PA and decreased heart rate and skin conductance reactivity, perhaps indicating dampened sympathetic function. The twin literature identified PA as a heritable trait, but little evidence implicates specific genes in the pathogenesis of PA. Neuroimaging studies of PA pinpoint impaired amygdala function in the assessment and conditioning of aversive stimuli, which may influence the establishment of behavioral patterns. Nodes of the default mode network were identified as possible neural correlates of PA, suggesting that altered function of this network may be involved in the genesis of PA. Given the overlap of PA with reactive aggression and the overall behavioral complexity of PA, it is clear that multiple endophenotypes of PA exist. This comprehensive review surveys the most salient neurobiologically informed research on PA.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".