Enculturation to musical pitch structure in young children: evidence from behavioral and electrophysiological methods
Bibliographic record
Abstract
Children learn the structure of the music of their culture similarly to how they learn the language to which they are exposed in their daily environment. Furthermore, as with language, children acquire this musical knowledge without formal instruction. Two critical aspects of musical pitch structure in Western tonal music are key membership (understanding which notes belong in a key and which do not) and harmony (understanding which notes combine to form chords and which notes and chords tend to follow others). The early developmental trajectory of the acquisition of this knowledge remains unclear, in part because of the difficulty of testing young children. In two experiments, we investigated 4- and 5-year-olds' enculturation to Western musical pitch using a novel age-appropriate and engaging behavioral task (Experiment 1) and electroencephalography (EEG; Experiment 2). In Experiment 1 we found behavioral evidence that 5-year-olds were sensitive to key membership but not to harmony, and no evidence that 4-year-olds were sensitive to either. However, in Experiment 2 we found neurophysiological evidence that 4-year-olds were sensitive to both key membership and harmony. Our results suggest that musical enculturation has a long developmental trajectory, and that children may have some knowledge of key membership and harmony before that knowledge can be expressed through explicit behavioral judgments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".