Evolution of Artistic and Athletic Propensities: Testing of Intersexual Selection and Intrasexual Competition
Bibliographic record
Abstract
Since Darwin proposed that human musicality evolved through sexual selection, empirical evidence has supported intersexual selection as one of the adaptive functions of artistic propensities. However, intrasexual competition has been overlooked. We tested their relative importance by investigating the relationship between the self-perceived talent/expertise in 16 artistic and 2 sports modalities and proxies of intersexual selection (i.e., mate value, mating and parenting efforts, sociosexuality, and number of sexual partners) and intrasexual competition (i.e., aggressiveness, intrasexual competitiveness) in heterosexuals. Participants were 82 Brazilian men, 166 Brazilian women, 146 Czech men, and 458 Czech women (Mage = 26.48, SD = 7.12). Factor analysis revealed five factors: Literary-arts (creative writing, humor, acting/theater/film, poetry, storytelling), Visual-arts (painting/drawing, sculpting, handcrafting, culinary arts, architecture design), Musical-arts (playing/instruments, singing, dance, whistling), Circus-arts (juggling, acrobatics), and Sports (individual, collective). Multivariate General Linear Model (GLM) showed more associations of the arts to intersexual selection in women and to intrasexual selection in men, and overall more relationships in women than in men. In women, literary and musical-arts were related to elevated inter- and intrasexual selections proxies, visual and circus-arts were related to elevated intersexual selection proxies, and sports were related to intrasexual selection proxies. In men, literary-arts and sports were related to elevated inter- and intrasexual selection proxies, musical-arts were related to intrasexual proxies, and circus-arts were related to intersexual proxies; visual-arts did not have predictors. Although present in both sexes, each sexual selection component has different relative importance in each sex. Artisticality functions to attract and maintain long/short-term partners, and to compete with mating rivals.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".