The Development of Rhythmic Categories as Revealed Through an Iterative Production Task
Bibliographic record
Abstract
Both humans and non-humans (e.g. birds and primates) preferentially produce and perceive auditory rhythms with simple integer ratios. In addition, these preferences (biases) tend to reflect specific integer-ratio rhythms that are common to one’s cultural listening experience. To better understand the developmental trajectory of these biases, we estimated children’s rhythm biases across the entire rhythm production space of simple (e.g., ratios of 1, 2, and 3) three-interval rhythms. North American children aged 6-11 years completed an iterative rhythm production task, in which they attempted to tap in synchrony with repeating three-interval rhythms chosen randomly from the space. For each rhythm, the child’s produced rhythm was presented back to them as the stimulus, and over the course of 5 such iterations we used their final reproductions to estimate their rhythmic biases or priors. Results suggest that regardless of the initial rhythm, after 5 iterations, children’s tapping converged on rhythms with (nearly) simple integer ratios, indicating that, like adults, their rhythmic priors consist of rhythms with simple-integer ratios. Furthermore, the relative weights (or prominence of different rhythmic priors) observed in children were highly correlated with those of adults. However, we also observed some age-related changes, especially for the ratio types that vary most across cultures. In an additional rhythm perception task, children were better at detecting rhythmic disruptions to a culturally familiar rhythm (in 4/4 meter with 2:1:1 ratio pattern) than to a culturally unfamiliar rhythm (7/8 meter with 3:2:2 ratios), and performance in this task was correlated with tapping variability in the iterative task. Taken together, our findings provide evidence that children as young as 6-years-old exhibit simple integer-ratio categorical rhythm priors in their rhythm production that closely resemble those of adults in the same culture.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".