Habilidades musicales y cognitivas en niños/as de entornos desfavorecidos
Bibliographic record
Abstract
Human beings are born with several abilities which are amenable to change. A growing number of studies have focused on the relations between musical and cognitive abilities but research with children from disadvantaged communities is scarce. This study explored the relations between musical and cognitive abilities in disadvantaged children. Participants were 169 children from deprived neighborhoods, attending the second year of primary education in public schools that do not offer music education. Children’s musical abilities (perception) were measured with the Melody, Rhythm, and Memory tests of Montreal Battery for the Evaluation of Musical Abilities and their cognitive abilities, with five WISC-III subtests (Similarities, Vocabulary, Cubes, Picture Arrangement, and Digits). Parental level of education was obtained from a questionnaire on the socio-economic status of children’s families. Results revealed (1) few and weak correlations between musical and cognitive abilities; (2) stronger correlations of Socioeconomic Status (SES) with cognitive than with musical abilities; (3) digit span predicts all musical abilities; 4) a clear factorial distinction between musical and cognitive abilities. Overall, results suggest that disadvantaged children’s musical and cognitive abilities, as measured by the present instruments, are partly independent regarding processing components.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".