Love, sacrifice, and rebirth: exploring the embodied narratives of retired women ballet dancers using life history interviews and body mapping
Bibliographic record
Abstract
Adopting a narrative constructionist lens, we conducted life history interviews and arts-based body mapping sessions with five retired women ballet dancers to examine how they storied their embodied experiences, both verbally and artistically. We constructed two narrative themes using narrative thematic and holistic-form structural analyses. (Embodied) Devotion: Love and Sacrifice explores the tensions between participants’ love for the artistry of ballet and the (physical) sacrifices they endured for success in dance, drawing on the performance and forward momentum narrative types. Illustrating these contradictions, on their body maps, participants included ballet-related symbols such as the colour pink and the bun hairstyle, but redrew their body outlines to be thinner and indicated areas of pain in red. Rising from the Ashes: Transformation and Contribution explored how participants drew on the quest meta-narrative, and the discovery and relational narrative types, to construct stories of personal growth and pedagogical reframing following ballet retirement. In conjunction with the symbols in the first theme, such stories were shown on the body maps through the symbolism of a tree and being traced in poses that ‘reach’ for the audience. These findings illustrate the role of cultural sport, body, and femininity narratives valorising performance, thinness, and discipline in shaping storytelling that rationalises and/or resists traditional ballet ideals. Methodologically, this research elucidates the body’s affordance as a medium for storytelling, foregrounding its capacity to articulate affective and shifting embodied experiences alongside verbal storytelling.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".