Testosterone mediates life‐history trade‐offs in female mammals
Bibliographic record
Abstract
Hormones mediate life-history trade-offs. In female mammals, such trade-offs have been studied predominantly in the contexts of oestrogen, progesterone and prolactin. We evaluate the hypothesis that prenatal and postnatal testosterone levels structure and regulate trade-offs in females involving components of reproduction and survival. This hypothesis is predicated on the observation that testosterone confers competition-related and survival-related benefits, but also reproduction-related costs, to female mammals. The hypothesis is supported by field and laboratory data from diverse non-human animals, and data from healthy women. Most broadly, relatively low testosterone level in females has been associated with earlier, faster and higher offspring production, greater attractiveness to males, and reduced dominance or competitiveness, whereas higher testosterone level is associated with delayed and reduced reproduction but increased dominance, status, aggression, and resource accrual. The magnitude of testosterone-mediated trade-offs is expected to depend upon the strength of female-female competition, which represents some function of species-specific ecology, behaviour and mating system. Testosterone-associated trade-offs have, until now, been virtually ignored in studies of female life history, reproductive physiology, evolutionary endocrinology, and female-limited disease, probably due to researcher biases towards conceptualizing androgens as hormones with effects mainly restricted to males.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".