Nepotism and subordinate tenure in a cooperative breeder
Bibliographic record
Abstract
In many cooperatively breeding societies, subordinate individuals delay dispersal and independent breeding. The length of time that subordinates delay dispersal (subordinate tenure) is likely to have important implications for both subordinate and dominant fitness. However, quantitative comparisons of the subordinate tenure of males and females are rare, especially with respect to the presence of same- versus opposite-sex close kin. Here, we investigate subordinate tenure and how it is affected by the genetic relationship between subordinates and dominants in the cooperatively breeding southern pied babbler (Turdoides bicolor). We find that for males, longer subordinate tenures result in increased likelihood of attaining dominance. In the presence of an unrelated dominant male, tenure of subordinate males is significantly shorter, indicating nepotism among males. Female tenures are unaffected by the genetic relationship to either the dominant male or female. These results are some of the first to demonstrate that the sex of both the dominants and subordinates, and the genetic relationship between them, can have significant impacts on subordinate tenure and dispersal delays. Nepotism has likely played a vital role in the evolution of cooperative breeding in this species.
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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 | 0.000 | 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) | 0.001 | 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".