Familiarity and homogeneity affect the discrimination of a song dialect
Bibliographic record
Abstract
Male songbirds of many species sing local song dialects that are restricted to defined geographical areas. In most tests of responses to local versus foreign dialects, males respond more aggressively to songs from their own dialect, presumably because local males represent more of a threat to their success. We asked how hearing foreign songs during development and territory establishment affects discrimination of the local dialect in wild Savannah sparrows, Passerculus sandwichensis. After foreign songs had been heard from loudspeakers in the study area in at least two consecutive breeding seasons, males reduced the intensity of their responses to the local version of the population-specific buzz segment of the song. Four years after the foreign songs were last broadcast on the study area, males again responded more aggressively to the local version of the buzz. As for the basis of these responses, we found no evidence that birds discriminated among dialects by comparing them to their own songs. However, auditory experience with a foreign song, whether during song development (from speaker-simulated song tutors) or during the current breeding season (from neighbours' songs), reduced the intensity of birds’ responses to the local buzz type. Both familiarity, in the form of auditory experience with a song type, and homogeneity, when a song type is sung by all or nearly all of the population, appear to contribute to heightened aggressive responses to a local song dialect.
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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 | 0.000 |
| 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) | 0.001 | 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".