Do Males Form Social Associations Based on Sexual Attractiveness in a Fission-Fusion Fish Society?
Bibliographic record
Abstract
Recent theory predicts that males should choose social environments that maximize their relative attractiveness to females by preferentially associating with less attractive rivals, so as to enhance their mating success. Using the Trinidadian guppy (Poecilia reticulata), a highly social species, we tested for non-random social associations among males in mixed-sex groups based on two phenotypic traits (body length and coloration) that predict relative sexual attractiveness to females and sexual (sperm) competitiveness. Based on a well-replicated laboratory dichotomous-choice test of social group preference, we could not reject the null hypothesis that focal males chose randomly between a mixed-sex group that comprised a female and a rival male that was less sexually attractive than themselves and another mixed-sex group containing a sexually more attractive male. The same conclusion was reached when females were absent from the two groups. As might be expected from these laboratory findings, free-ranging males in the field were not assorted by either body length or colour in mixed-sex shoals. The apparent lack of an evolved and expressed preference in wild male guppies from our study population to form social associations with other males based on their relative sexual attractiveness and competitiveness might be due to the fission-fusion dynamics of guppy shoals in nature. Such social dynamics likely places constraints on the formation of stable phenotype-based social associations among males. This possibility is supported by a simulation model which assumes group departure rules based on relative body size and coloration in 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".