Pervasive patterns in the songs of passerine birds resemble human music universals and are linked with production and cognitive mechanisms
Bibliographic record
Abstract
Abstract Music is a complex learned behavior that is ubiquitous among humans, and many musical patterns are shared across geography and cultures (“music universals”). Knowing whether these universals are specific to humans or shared with other animals is important to understand how production-related factors (motor biases and constraints) or cognitive factors (learning) contribute to the emergence of these acoustic patterns. Bird song is often described as an animal analogue of human music, and some studies of individual avian species highlight acoustic similarities between bird song and music. However, expansive and comparative approaches are necessary to identify universal patterns within bird song, reveal mechanisms associated with these patterns, and draw parallels to music universals. Here, we adopt such an approach and analyze the prevalence of acoustic patterns (sequences) across ∼300 species of passerines, spanning both oscines (songbirds; vocal learners) and their sister clade, suboscines (passerines that produce songs that are not learned), as well as within a global corpus of human vocal music. This approach allowed us to directly test hypotheses that phonation mechanisms or vocal learning shape the emergence of universal patterns. We first document acoustic patterns that were widely shared across passerines and similar to music universals (e.g., small pitch intervals), highlighting the role of shared vocal production mechanisms in these patterns. Consistent with a contribution of vocal learning, we observed patterns (e.g., alternation in durations) there were more similar between oscines and humans than between suboscines and humans. Interestingly, we also discovered patterns (e.g., pitch alternation) that were inconsistent with a contribution of vocal learning and were more similar between suboscines and humans than between oscines and humans. This research provides the broadest evidence of shared universals in vocal performance across birds and humans and highlights convergent mechanisms shaping communication patterns.
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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 | 0.001 |
| 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".