Reciprocal social ties drive stability within a social network
Bibliographic record
Abstract
ABSTRACT Social reciprocity is thought to be the most important driver of cooperation among non-kin, but its effects within complex social networks where individuals choose their partners have not been studied. Here, we test whether reciprocation can explain social dynamics in a bird species where males form coalitions to court females, the wire-tailed manakin ( Pipra filicauda ). In our study population, approximately a third of male-male social interactions involve one male leaving his territory to interact and display with the owner of another territory; this directional behaviour provides benefits to the recipient at a cost to the visiting male. We characterize social ties among pairs of territory holders according to the directionality of their interactions, and show here that territory holding males engaged in far more reciprocated (bidirectional) partnerships with other territory holders than expected by chance. Reciprocated partnerships were also stronger (i.e., the partners interacted more frequently) than non-reciprocated partnerships, controlling for spatial proximity of the territories. An individual-level analysis revealed that a male’s social contribution to a given partner was predictive of the number of social interactions he received from that same partner. Finally, we show that reciprocation predicted the long-term stability of social partnerships one year later. Together, these results demonstrate that reciprocity is associated with stability in complex social networks where partner choice is flexible. LAY SUMMARY When animals are free to choose their partners, how does reciprocity influence social dynamics? In the wire-tailed manakin, males form coalitions with other males to help attract mates. We tracked male social networks and found that some males form reciprocal partnerships where each male leaves its territory to display at the other’s territory. These bidirectional partnerships are particularly strong and stable, indicating that reciprocity is associated with stability in complex social networks.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".