Sex differences in razorbill <i>Alca torda</i> parent—offspring vocal recognition
Bibliographic record
Abstract
We investigated differences in parent-offspring vocal recognition between males and females in a natural population of razorbills Alca torda, a long-lived and highly social species of auk (Family: Alcidae). Razorbills provide biparental care to their chicks while at the nest site, after which the male is the sole caregiver for an additional period at sea. Parent-offspring recognition in razorbills is most challenging once the chick becomes mobile, leaves the nest site and goes to sea with the male parent. It is during this period when selection pressure acting on recognition behaviour is expected to be strongest. As a result, we predicted that parent-offspring recognition would be better developed in the male parent, that is, show a paternal bias. To test this prediction we used vocal playback experiments conducted on breeding razorbills at the Gannet Islands, Labrador, Canada. We found (1) most positive responses to playbacks (vocal and phonotactic) occurred close to fledging, (2) males responded more to calls from their chicks than to calls from strange chicks, (3) females responded indifferently to calls from their own or strange chicks and (4) chicks responded more to calls from their male parent than to calls from other adult males. The results provide clear evidence of mutual vocal recognition between the male parent and the chick but not between the female parent and the chick, supporting the prediction that parent-offspring recognition is male biased in this species. Such a bias could have important social implications for a variety of behavioural and basic life history traits such as cooperation and sex-biased dispersal.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".