The evolution of female ornaments and weaponry: social selection, sexual selection and ecological competition
Bibliographic record
Abstract
Ornaments, weapons and aggressive behaviours may evolve in female animals by mate choice and intrasexual competition for mating opportunities-the standard forms of sexual selection in males. However, a growing body of evidence suggests that selection tends to operate in different ways in males and females, with female traits more often mediating competition for ecological resources, rather than mate acquisition. Two main solutions have been proposed to accommodate this disparity. One is to expand the concept of sexual selection to include all mechanisms related to fecundity; another is to adopt an alternative conceptual framework-the theory of social selection-in which sexual selection is one component of a more general form of selection resulting from all social interactions. In this study, we summarize the history of the debate about female ornaments and weapons, and discuss potential resolutions. We review the components of fitness driving ornamentation in a wide range of systems, and show that selection often falls outside the limits of traditional sexual selection theory, particularly in females. We conclude that the evolution of these traits in both sexes is best understood within the unifying framework of social selection.
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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) | 0.001 | 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 | 0.001 |
| 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".