Individual differences in musical ability are stable over time in childhood
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The development of human abilities stems from a complex interplay between genetic predispositions and environmental factors. Numerous studies have compared musicians with non-musicians on measures of musical and non-musical ability, frequently attributing musicians' superior performance to their training. By ignoring preexisting differences, however, this view assumes that taking music lessons is akin to random assignment. In the present longitudinal study, the musical ability of 5- to 10-year-olds was measured at Time 1 with a test of music perception and cognition. Five years later, at Time 2, the children took the same test and a second test designed for older listeners. The test-retest correlation for aggregate scores was remarkably high, r ≈ 0.7, and remained strong when confounding variables (age, cognitive abilities, personality) were held constant. At both time points, music training was associated with musical ability, but the association at Time 2 became nonsignificant when musical ability at Time 1 was held constant. Time 1 musical ability also predicted duration of subsequent music training. These data are consistent with results from genetic studies, which implicate genes in all aspects of musical behavior and achievement, and with meta-analyses, which indicate that transfer effects from music training are weak. In short, early musical abilities significantly predicted later abilities, demonstrating that individual differences are stable over time. We found no evidence, however, to suggest that music training predicted musical ability after accounting for prior ability. The results underscore the importance of considering preexisting abilities in any type of learning.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it