Deceptive Copulation Calls Attract Female Visitors to Peacock Leks
Bibliographic record
Abstract
Theory holds that dishonest signaling can be stable if it is rare. We report here that some peacocks perform specialized copulation calls (hoots) when females are not present and the peacocks are clearly not attempting to copulate. Because these solo hoots are almost always given out of view of females, they may be dishonest signals of male mating attempts. These dishonest calls are surprisingly common, making up about a third of all hoot calls in our study populations. Females are more likely to visit males after they give a solo hoot call, and we confirm using a playback experiment that females are attracted to the sound of the hoot. Our findings suggest that both sexes use the hoot call tactically: females to locate potential mates and males to attract female visitors. We suggest that the solo hoot may be a deceptive signal that is acquired and maintained through reward-based learning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".