Bibliographic record
Abstract
Professional, contemporary dancers typically transition into another role or industry when their bodies begin to show signs of ageing in their mid-30s. In ‘Physical and Mental Demands Experienced by Ageing Dancers: Strategies and values’, the dance dramaturg and scholar Pil Hansen and the dance scientist Sarah J. Kenny take a close look at how dancers who continue to dance past this point and into their 60s, experience and meet the demands of professional dance praxis. Through a qualitative pilot study with three ageing Canadian dancers, Hansen and Kenny identify common demanding factors and strategies that these ageing dancers have developed to address them. When discussed in light of related studies, results indicate that interactions between a set of material, discursive and physical factors need to be addressed to help dancers build long-life careers. Findings also suggest the possibility that advanced cognitive and artistic strategies may provide essential support for the mature dancer’s physical practice and expressivity while countering the cognitive decline otherwise caused by ageing. It will require a multi-disciplinary research effort, involving a larger group of participants, to further understand the perceived demands and strategies utilized by aging dancers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".