Health Education Literacy and Accessibility for Musicians: A Global Approach. Report from the Worldwide Universities Network Project
Bibliographic record
Abstract
OBJECTIVE: To address the need for accessible health education and improved health literacy for musicians throughout their lifespan. METHODS: Formation of a multicultural, international, and interdisciplinary collaborative research team, funded by the Worldwide Universities Network. The goal is to design a multi-strand research program to develop flexible and accessible approaches to health education for musicians, thus improving their health literacy. RESULTS: Two team meetings took place in 2018. The first was held 11 to 15 April 2018 in Perth, Australia, and involved a review of existing literature and interventions on health education in music schools, intensive development of research topics, aims, and methodologies, and identification of potential funding sources to support future large-scale research programs. This resulted in the draft design of three research projects, finalized during a second meeting in Maastricht, the Netherlands, 27 to 31 August 2018. DISCUSSION: These intensive meetings identified the need for both cultural change in music education settings as well as improved health literacy in musicians across global geographical regions. A global project to address health literacy and health education accessibility for musicians has commenced.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".