Bibliographic record
Abstract
This study investigates the evolution of the sex ratio (parental investment in sons) when breeding adults are supported by help provided by nonbreeding individuals of one sex. The study also assumes that the helping sex remains on its natal site to compete for the opportunity to breed, whereas the nonhelping sex disperses. Two kin-selection models are presented, both of which incorporate the age structure found in many natural populations where such helping occurs. The first model assumes that helpers increase the survival of their parents. The second model assumes that helpers are indiscriminant: a helper chooses to increase the survival of a random pair of adults breeding on its natal patch. In both models, sex ratios are not always biased toward the sex that provides the most help. When helpers do not discriminate (second model), the direction of sex-ratio bias is determined solely by the size of the benefit of helping behavior. When this benefit is small, sex-ratio evolution is primarily influenced by local resource competition and sex ratios are biased toward the nonhelping (dispersive) sex. If the benefit of help is large enough, the effect of local resource competition is reduced and sex-ratio bias favors the helpful sex. When helpers help only their parents, the same qualitative relationship exists between the direction of sex-ratio bias and the benefit of helping. In this case, however, the direction of sex-ratio bias is also influenced by the size of the social group, mortality, and which individual (mother or father) controls the sex ratio. This study also investigates a sex-ratio conflict that exists between mates. Helping behavior of nonbreeders can act to alleviate the disparities between the optimal sex ratio from the perspective of a mother and that from the perspective of a father. This consequence of helping has not been previously recognized.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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 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".