Selective social tolerance drives differentiated relationships among wild female chimpanzees
Bibliographic record
Abstract
Strong, affiliative bonds often function to facilitate social competition through cooperative defence of resources, but the benefits of social bonds may be low when direct competition is less intense or less beneficial. In such cases, one possible outcome is that relationships are weak and undifferentiated. Alternatively, negotiating stable, selectively tolerant relationships may be a strategy to mitigate the costs and risks of sharing space when direct competition is undesirable. We investigated dyadic social tolerance among wild adult female chimpanzees, who engage in low rates of affiliation and aggression amongst one another. While females associate with one another at different rates, these patterns could reflect shared patterns of behaviour (e.g., ranging) rather than social preference or variation in relationship quality. We first determined whether patterns of dyadic spatial association (five-meter proximity) were differentiated and stable over time. To assess whether dyadic spatial association reflected preference and variation in social tolerance, we tested whether spatial association was actively maintained by waiting and following behaviour, and associated with decreased aggression and increased cofeeding. Spatial associations were differentiated, and stronger associations were more stable. Frequent associates used following and waiting behaviour to actively maintain associations. Association positively predicted time cofeeding and negatively predicted aggression. These patterns were true among related and unrelated dyads. Among unrelated females, dyads with stronger associations maintained proximity more mutually. This study highlights social tolerance as a stable relationship attribute that can predict and explain patterns of behaviour and social network structure, distinct from, or in the absence of, affiliation.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".