Females allocate differentially to offspring size and number in response to male effects on female and offspring fitness
Bibliographic record
Abstract
Female investment in offspring size and number has been observed to vary with the phenotype of their mate across diverse taxa. Recent theory motivated by these intriguing empirical patterns predicted both positive (differential allocation) and negative (reproductive compensation) effects of mating with a preferred male on female investment. These predictions, however, focused on total reproductive effort and did not distinguish between a response in offspring size and clutch size. Here, we model how specific paternal effects on fitness affect maternal allocation to offspring size and number. The specific mechanism by which males affect the fitness of females or their offspring determines whether and how females allocated differentially. Offspring size is predicted to increase when males benefit offspring survival, but decrease when males increase offspring growth rate. Clutch size is predicted to increase when males contribute to female resources (e.g. with a nuptial gift) and when males increase offspring growth rate. The predicted direction and magnitude of female responses vary with female age, but only when per-offspring paternal benefits decline with clutch size. We conclude that considering specific paternal effects on fitness in the context of maternal life-history trade-offs can help explain mixed empirical patterns of differential allocation and reproductive compensation.
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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 | 0.001 |
| 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) | 0.000 | 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".