An inconvenient tooth: Evaluating female choice in multiple paternity using an evolutionarily and ecologically important vertebrate clade
Bibliographic record
Abstract
Understanding mating systems is a pillar of behavioural ecology, placing the complex interactions between females and males into a reproductive context. The field of multiple paternity, the phenomenon whereby many sires contribute to an individual litter, has traditionally viewed females as passive players in a male-male competitive framework. With the emergence of feminist perspectives in ecological fields, novel alternative mechanisms and evolutionary theories across invertebrate and vertebrate taxa recognize females are active stakeholders in the reproductive process. Despite their evolutionary significance, ecological diversity and myriad reproductive modes, elasmobranch (sharks, skates and rays) research lags behind other fields regarding complex biological processes, such as multiple paternity which is often ascribed to convenience polyandry. Here, we layout hypotheses and resynthesize multiple paternity literature from a female and life history perspective to highlight how alternative mechanisms influence the predominance of multiple paternity across elasmobranchs. We draw upon parallels in other invertebrate and vertebrate taxa to demonstrate how female elasmobranchs can influence multiple paternity outcomes that benefit their reproductive success. Our article challenges dogma that has resulted from years of dismissing the female perspective as important and provides a framework for future advancement using more holistic approaches to studying mating systems.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".