Darwin Versus Wallace: Esthetic Evolution and Preferential Mate Choice
Bibliographic record
Abstract
Dominant theorizing and research surrounding the operation of intersexual selection in evolutionary psychology tends to be guided by an adaptationist framework and aligned with models of sexual selection involving direct benefits (e.g., parental care) and indirect “good gene” and condition-dependent benefits. In this way, evolutionary psychologists more often espouse Alfred Russel Wallaces’ utilitarian viewpoint that traits become attractive because they honestly signal vigor and vitality, which gives priority to natural selection. In doing so, Darwin’s esthetic perspective originally articulated inThe Descent of Manand alternative models of sexual selection (e.g., Fisherian runaway), are given less consideration. This is despite some informative reviews on the topic in evolutionary psychology. In the current conceptual analysis, we discuss the potential of Prum’s Lande-Kirkpatrick (LK) null model of sexual selection to help make sense of some of the mixed evidence regarding the links between attractive traits and purported markers of phenotypic and genetic condition. We then consider how the implications of the LK null model can help to shift theoretical assumptions and guide future work in evolutionary psychology on intersexual 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".