ENSINAR EXIGE ESCUTAR: UMA REFLEXÃO SOBRE ENSINO-APRENDIZAGEM E ECOLOGIA ACÚSTICA NAS ESCOLAS DE ARARAS-SP
Bibliographic record
Abstract
In this article we intend to look into the soundscapes of schools in the city of Araras-SP and reflect on how their sounds can influence the teaching-learning process. For that, we will use a scientific literature review and a field study based on the experience of the author teachers who work in the teaching staff of the Municipal Education Network. We will approach the concept of soundscape, based on the theory of Canadian composer and educator R. Murray Schafer, who seeks to analyze in his works the unbridled growth of noise pollution in our contemporary life. Ultimately, proposals are sought to build a school environment that thinks about acoustic ecology, to make this pedagogical space more pleasant, where people can learn from each other. intend to synthesize Schafer's thoughts and connect them with a proposal to improve communication in schools, an education
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".