Population differences in behaviour are explained by shared within‐population trait correlations
Bibliographic record
Abstract
Correlations in behavioural traits across time, situation and ecological context (i.e. 'behavioural syndromes' or 'personality') have been documented for a variety of behaviours, and in diverse taxa. Perhaps the most controversial inference from the behavioural syndromes literature is that correlated behaviour may act as an evolutionary constraint and evolutionary change in one's behaviour may necessarily involve shifts in others. We test the two predictions of this hypothesis using comparative data from eighteen populations of the socially polymorphic spider, Anelosimus studiosus (Araneae, Theriidae). First, we ask whether geographically distant populations share a common syndrome. Second, we test whether population differences in behaviour are correlated similarly to within-population trait correlations. Our results reveal that populations separated by as much as 36 degrees latitude shared similar syndromes. Furthermore, population differences in behaviour were correlated in the same manner as within-population trait correlations. That is, population divergence tended to be along the same axes as within-population covariance. Together, these results suggest a lack of evolutionary independence in the syndrome's constituent traits.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".