Sustained musical beat perception develops into late childhood and predicts phonological abilities.
Bibliographic record
Abstract
Sensitivity to auditory rhythmic structures in music and language is evident as early as infancy, but performance on beat perception tasks is often well below adult levels and improves gradually with age. While some research has suggested the ability to perceive musical beat develops early, even in infancy, it remains unclear whether adult-like perception of musical beat is present in children. The capacity to sustain an internal sense of the beat is critical for various rhythmic musical behaviors, yet very little is known about the development of this ability. In this study, 223 participants ranging in age from 4 to 23 years from the Las Vegas, Nevada, community completed a musical beat discrimination task, during which they first listened to a strongly metrical musical excerpt and then attempted to sustain their perception of the musical beat while listening to a repeated, beat-ambiguous rhythm for up to 14.4 s. They then indicated whether a drum probe matched or did not match the beat. Results suggested that the ability to identify the matching probe improved throughout middle childhood (8-9 years) and did not reach adult-like levels until adolescence (12-14 years). Furthermore, scores on the beat perception task were positively related to phonological processing, after accounting for age, short-term memory, and music and dance training. This study lends further support to the notion that children's capacity for beat perception is not fully developed until adolescence and suggests we should reconsider assumptions of musical beat mastery by infants and young children. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".