Cross-cultural influences on rhythm processing: reproduction, discrimination, and beat tapping
Bibliographic record
Abstract
The structures of musical rhythm differ between cultures, despite the fact that the ability to entrain movement to musical rhythm occurs in virtually all individuals across cultures. To measure the influence of culture on rhythm processing, we tested East African and North American adults on perception, production, and beat tapping for rhythms derived from East African and Western music. To assess rhythm perception, participants identified whether pairs of rhythms were the same or different. To assess rhythm production, participants reproduced rhythms after hearing them. To assess beat tapping, participants tapped the beat along with repeated rhythms. We expected that performance in all three tasks would be influenced by the culture of the participant and the culture of the rhythm. Specifically, we predicted that a participant's ability to discriminate, reproduce, and accurately tap the beat would be better for rhythms from their own culture than for rhythms from another culture. In the rhythm discrimination task, there were no differences in discriminating culturally familiar and unfamiliar rhythms. In the rhythm reproduction task, both groups reproduced East African rhythms more accurately than Western rhythms, but East African participants also showed an effect of cultural familiarity, leading to a significant interaction. In the beat tapping task, participants in both groups tapped the beat more accurately for culturally familiar than for unfamiliar rhythms. Moreover, there were differences between the two participant groups, and between the two types of rhythms, in the metrical level selected for beat tapping. The results demonstrate that culture does influence the processing of musical rhythm. In terms of the function of musical rhythm, our results are consistent with theories that musical rhythm enables synchronization. Musical rhythm may foster musical cultural identity by enabling within-group synchronization to music, perhaps supporting social cohesion.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".