The Social Organization of Post-Secondary Music Students’ Work and Health: An Institutional Ethnography Protocol
Why this work is in the frame
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Bibliographic record
Abstract
Researchers have found that many post-secondary music students suffer from physical and mental health issues. However, researchers have mainly studied these problems at the individual level, with little investigation of how music students’ work is shaped by the coordinating effects of policies, texts, and discourses at and beyond their local site. This paper describes a protocol for an international project that will explore the health of music students in the context of their daily work. Using an institutional ethnography approach, we will examine the social organization of music students’ work at three universities: two in Canada and one in Australia. This will be the first set of studies that use institutional ethnography specifically for the purpose of understanding how the social organization of music students’ work shapes their health. Data will be collected using several methods common to institutional ethnography: interviews, focus groups, observations, and collecting texts. Data analysis will begin during the data collection process and proceed in two fluid stages. The first stage will involve a detailed investigation of the pertinent work activities at each music school. The second will involve linking that work to specific social relations within and beyond the institution. After data analysis has been completed at all three sites, findings will be compared to one another to identify commonalities and differences in how students’ work is organized. Findings of the entire project may inform policy-making and lead to positive change at the institutions studied, as well as others where similar social organization may occur. The novel approach described here will provide opportunities to expand current knowledge about music students’ work and health beyond what has been learned through approaches that focus on students’ individual behaviours and attributes.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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