The influence of mating system on the intensity of parent–offspring conflict in primates
Bibliographic record
Abstract
An evolutionary conflict of interest exists between parents and their offspring over the partitioning of parental investment (PI) among siblings. When the direct fitness benefits to offspring of increased PI, outweigh the inclusive fitness costs from lost future sibling fitness, selection should favour the evolution of offspring selfishness over altruism. In theory, this conflict is heightened when females are not strictly monogamous, as current offspring should be less altruistic towards future half-siblings than they would be towards full-siblings. Using data collected on foetal growth rate (representing prenatal PI) in primates, I test the prediction from theory that the resolution of the parent-offspring conflict will be closer to the offspring's evolutionary optima in polyandrous species than in more monandrous species. Using phylogenetic comparative analysis, and controlling for allometry, I show that offspring are able to obtain more PI when the probability of future full-siblings decreases, and that this is most pronounced in taxa where there is the opportunity for direct foetal access to the maternal bloodstream. These results support the hypothesis that the resolution of prenatal PI conflict is influenced by both a species' mating system and by its placental structure.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".