Young children pause on phrase boundaries in self-paced music listening: The role of harmonic cues.
Bibliographic record
Abstract
Proper segmentation of auditory streams is essential for understanding music. Many cues, including meter, melodic contour, and harmony, influence adults' perception of musical phrase boundaries. To date, no studies have examined young children's musical grouping in a production task. We used a musical self-pacing method to investigate (1) whether dwell times index young children's musical phrase grouping and, if so, (2) whether children dwell longer on phrase boundaries defined by harmonic cues specifically. In Experiment 1, we asked 3-year-old children to self-pace through chord progressions from Bach chorales (sequences in which metrical, harmonic, and melodic contour grouping cues aligned) by pressing a computer key to present each chord in the sequence. Participants dwelled longer on chords in the 8th position, which corresponded to phrase endings. In Experiment 2, we tested 3-, 4-, and 7-year-old children's sensitivity to harmonic cues to phrase grouping when metrical regularity cues and melodic contour cues were misaligned with the harmonic phrase boundaries. In this case, 7 and 4 year olds but not 3 year olds dwelled longer on harmonic phrase boundaries, suggesting that the influence of harmonic cues on phrase boundary perception develops substantially between 3 and 4 years of age in Western children. Overall, we show that the musical dwell time method is child-friendly and can be used to investigate various aspects of young children's musical understanding, including phrase grouping and harmonic knowledge. (PsycINFO Database Record
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".