Heritable victimization and the benefits of agonistic relationships
Bibliographic record
Abstract
Here, we present estimates of heritability and selection on network traits in a single population, allowing us to address the evolutionary potential of social behavior and the poorly understood link between sociality and fitness. To evolve, sociality must have some heritable basis, yet the heritability of social relationships is largely unknown. Recent advances in both social network analyses and quantitative genetics allow us to quantify attributes of social relationships and estimate their heritability in free-living populations. Our analyses addressed a variety of measures (in-degree, out-degree, attractiveness, expansiveness, embeddedness, and betweenness), and we hypothesized that traits reflecting relationships controlled by an individual (i.e., those that the individual initiated or were directly involved in) would be more heritable than those based largely on the behavior of conspecifics. Identifying patterns of heritability and selection among related traits may provide insight into which types of relationships are important in animal societies. As expected, we found that variation in indirect measures was largely explained by nongenetic variation. Yet, surprisingly, traits capturing initiated interactions do not possess significant additive genetic variation, whereas measures of received interactions are heritable. Measures describing initiated aggression and position in an agonistic network are under selection (0.3 < |S| < 0.4), although advantageous trait values are not inherited by offspring. It appears that agonistic relationships positively influence fitness and seemingly costly or harmful ties may, in fact, be beneficial. Our study highlights the importance of studying agonistic as well as affiliative relationships to understand fully the connections between sociality and fitness.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| 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".