SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS
Bibliographic record
Abstract
ii This qualitative study explores how the health and wellness of workers in a relatively low status physical occupation-- in this case professional dancers in Western Canada-- is understood, managed and negotiated within its specific occupational culture. These embodied workers are at risk of pain, injury and other body-related issues, including image and eating issues, in the pursuit of career goals. In-depth interviews with professional theatrical dancers employed in company settings and working as independent artists, and a limited number of clinicians who treat dancers, were conducted. Drawing upon literature from the sociology of dance, sport, health and illness, and work, and framing the discussion in terms of the dramaturgical, phenomenological, and art world perspectives, this project details the lived, embodied experiences of this specific group of workers. A number of important themes (e.g., how pain and injury are hidden and downplayed in a culture of risk, how impressions and potential stigmas related to damaged bodies are managed, how embodied identity is impacted by injury experiences, and how the relationship between dancers and clinicians is negotiated) are explored.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.639 | 0.331 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".