Perceptions of Pain, Injury, and Transition-Retirement
Bibliographic record
Abstract
Dancers are often referred to as "athletes of the arts," and like other athletes they undergo years of hard physical training in pursuit of excellence. Previous research has indicated that dancers develop high pain thresholds and push past their pain barriers. This has potential implications for their health and wellbeing in both their professional careers and life after dance. Therefore, the purpose of this pilot study was to explore the perceptions and experiences of injury, pain, and retirement among professional dancers. Twenty professional dancers, 10 from the United Kingdom and Canada, hereafter referred to as "international," and 10 from Australia participated in a semi-structured interview reflecting on their experiences of the aforementioned issues. The following themes were identified: 1. the injured dancer: the reality; 2. dancers' perceptions and experiences of pain; 3. the transition leading to retirement; and 4. life after dance: attributes facilitating career change. Results from both Australian and international dancers revealed that they withstand, manage, and dance through persistent levels of pain and injury. All participants reported that they were highly motivated and dedicated to their dance careers; however, the majority of Australian dancers were not adequately prepared for, or aware of, the challenges of transition into their post-professional dance lives when compared to the international dancers. Dancer transition organizations currently operate in America, the Netherlands, Canada, and the United Kingdom and serve as valuable models that could be replicated in Australia. The current study recommends increased awareness of pain management and injury prevention strategies for dancers and further supports the rationale for development and implementation of transition models for dancers in Australia and elsewhere.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".