Inteligencia musical, rendimiento escolar y desarrollo integral en educación primaria
Bibliographic record
Abstract
This research we pretend to design an intervention program to improve musical intelligence \nand auditive discrimination, enhancing school performance and the rest of intelligences. \nFirst, a sample of 30 children of second grade of primary school was used. The level of \nperformance of the different intelligences was analyzed through Multiple Intelligences \nQuestionnaire (Armstrong, 2001). Secondly, the level of auditive discrimination was assessed \nwith the auditive discrimination test (PAF) of Arándiga (1999). Finally, the level of \nschool performance for the quarter and music subject were identified based on the data \nprovided by the tutors. The results showed that the group has a low level of musical intelligence \ncompared with the rest of intelligences and medium school performance. Conversely, \na large majority of the group has obtained a high level of auditive discrimination. As a \nresult, we have designed an intervention program to improve the evaluated aspects.
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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 | 0.001 | 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) | 0.005 | 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".