Cohesion in male singing behavior predicts group reproductive output in a social songbird
Bibliographic record
Abstract
Summary All social groups require organization to function optimally. Group organization is often shaped by social ‘rules’, which function to manage conflict, discourage cheating, or promote cooperation 1–5 . If social rules promote effective social living, then the ability to learn and follow these rules may be expected to influence individual and group-level fitness. However, such links can rarely be tested, due to the complexity of the factors mediating social systems and the difficulty of gathering data across multiple groups. Songbirds offer an opportunity to investigate the link between social rules and reproductive output because most of their social interactions are mediated by song, a well-studied and readily quantifiable behavior 6,7 . Using observations from 19 groups of brown-headed cowbirds ( Molothrus ater ) studied across 15 years, we find evidence for a previously undocumented social rule: cohesive group transitions between dominance- and courtship-related singing. Comparing across groups, the degree of cohesion in male singing behavior predicts the reproductive output of their group. Experimental manipulation of group structure via the introduction of juvenile males to captive flocks reduced group cohesion and adult male reproductive success. Taken together, these results demonstrate that cohesion in group behavioral states can affect both individual and group-level reproductive success, suggesting that selection can act not only on individual-level traits, but also on an individual’s ability and opportunity to participate effectively in organized social interactions. Social cohesion could therefore be an unappreciated force affecting social evolution in many diverse systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".