Sex differences in the relationship between aggressiveness and the strength of handedness in humans
Bibliographic record
Abstract
Cerebral lateralisation, the partitioning of cognitive functioning into one hemisphere of the brain, was once considered unique to humans; however, recent research in a variety of taxa suggests that lateralisation is an evolutionarily ancient adaptation. Handedness is the most obvious manifestation of cerebral lateralisation in humans. Much of the literature on handedness has focused on the direction, rather than the strength, of this lateralisation. From both genetic and evolutionary perspectives it may be more informative to study degrees of cerebral lateralisation rather than direction. Strong evidence suggests that the strength may be more closely associated with individual differences in behaviour in humans than the direction, and individual variation in the degree of lateralisation has been found to correlate with personality-like characteristics such as aggressiveness in fish. The association between different patterns of lateralisation and personality characteristics may help explain how variation in the strength of lateralisation is evolutionarily stable in natural populations. The present study investigated the relationship between aggression and strength of handedness in humans. We found a significant interaction between sex and lateralisation with respect to aggression. In males, trait aggression was significantly higher in strong-handers than in mixed-handers, while no difference was seen in females. This finding highlights the importance of considering sex as a factor when investigating relationships between cerebral lateralisation and personality characteristics. Potential causes and consequences of the sex interaction as well as future directions for research are discussed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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".