Escalation, Retreat, and Female Indifference as Alternative Outcomes of Sexually Antagonistic Coevolution
Bibliographic record
Abstract
Verbal and quantitative genetic models of sexually antagonistic coevolution suggest that coevolutionary arms races should be common. Sexual selection favors exaggeration of male persistence traits that are costly to females, and females, in turn, are selected to resist these traits. The heightened resistance by females is thought to then favor further exaggeration in the male trait, leading to an escalating coevolutionary arms race between persistence and resistance traits. Much of this theory, however, is based on an (implicit) assumption that there are tight constraints on how female resistance can evolve. We develop a theory that identifies and relaxes these constraints, allowing female resistance to evolve in a fashion that better reflects known empirical patterns in the evolution of female preference functions (the resistance trait). Our results suggest that evolutionary arms races that lead to the exaggeration of persistence and resistance will be much less common than formerly predicted. Females sometimes evolve indifference to male traits rather than resistance and can even evolve to discriminate against these traits. These alternative outcomes depend on the existence of genetic variance in the components of the female sensory system underlying female resistance and on the strength of natural selection acting on these components. Female indifference tends to evolve when natural selection on the sensory system is weak, and under these conditions, sexually antagonistic coevolution tends not to reduce female fitness significantly at equilibrium. When natural selection on the female sensory system is strong, however, then arms races are more likely, and female fitness is then sometimes significantly depressed at equilibrium. Sexually antagonistic coevolution is thus likely to have strong deleterious effects on population fitness only when female sensory traits are under strong natural selection to perform functions in addition to those involved with mating. Together, these results suggest that identifying the nature of genetic variation in and the strength of natural selection on female resistance should be a central goal of future studies of sexual conflict.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".