Behavioural Consistency in Female Resistance to Male Harassment in a Water Strider Species
Bibliographic record
Abstract
Abstract Sexual conflict over mating rate often implies that males persist at frequently harassing females to gain matings while females resist mating attempts. In water striders, females can resist by engaging in vigorous pre‐copulatory struggles to dislodge males, but alternative means of resistance have seldom been investigated. Contrary to males, female resistance has not been investigated as a repeatable behaviour. We used Gerris buenoi to investigate the capacity to abbreviate struggles and the tendency to hide off the water as two potential female resistance traits. Specifically, we asked whether these behaviours are repeatable and whether they vary according to sexual conflict intensity and past mating experience. Also, we studied the possible connections between these behaviours and traits linked to fitness, namely endured harassment and mating activity. The capacity to abbreviate struggles was poorly repeatable and decreased with sexual conflict intensity and endured harassment. It seems to be mainly determined by the social environment and by recent events related to sexual conflict. The tendency to hide off the water was significantly repeatable across sexual conflict intensities and can be considered as a repeatable behaviour. Hiding frequently off the water allowed females to decrease the harassment endured by females and may enhance female fitness. In nature, hiding is more readily and more frequently observed than pre‐copulatory struggles. Directly associating hiding off water with female fitness would confirm that this consistent phenotype contributes to sexually antagonistic female resistance.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".