Do Female Garter Snakes Evade Males to Avoid Harassment or to Enhance Mate Quality?
Bibliographic record
Abstract
Females of many species behave in ways that make it difficult for males to locate, court, and inseminate them. Two hypotheses have been advanced to explain such behavior: either a female thereby minimizes costs of harassment (sexual conflict model) or by playing "hard to get" she discourages inferior suitors (indirect mate choice model). Our studies of garter snakes (Thamnophis sirtalis parietalis) at a communal den in Manitoba support an interpretation of sexual conflict rather than indirect mate choice. Female snakes dispersed rapidly from the den through areas with relatively few males rather than waiting for additional courtship. Many females dispersed without mating. Experimental (pheromonal) manipulation of the intensity of courtship accelerated rates of female dispersal rather than delaying dispersal, as would be predicted if females wait to obtain matings. The behaviors of females escaping from courting groups were maximally effective in losing their suitors regardless of the number of courting males or whether or not the female was capable of mating (recently mated females cannot mate again because of a mating plug). In total, our data are most consistent with the hypothesis that female garter snakes at communal dens evade males to escape harassment rather than to enhance mate quality.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".