Stories of physical activity and disability: exploring sport and exercise students’ narrative imagination through story completion
Bibliographic record
Abstract
Sport and exercise students will form the next generation of sport, exercise and health practitioners tasked with supporting disabled people to be physically active. Yet, little is known about what these students imagine about physical activity and disability. This focus is important as university can be a narratively rich environment that offers pedagogical opportunities to understand and disrupt dangerous narratives around disability and amplify alternative narratives. The aim of this study was to explore sport and exercise students’ narrative imagination of physical activity and disability through the novel method of story completion. Ninety Uk-based participants wrote a story in response to one of four story stems. Following a rigorously applied holistic-form structural analysis, three principal narratives were identified across all stories: 1) incapability narrative; 2) supercrip narrative; and 3) social justice in sport narrative. Novel narrative insights highlighted the problematic dominant representations of disabled people in incapability and supercrip stories underpinned by an ableist ideology and emphasised the need to amplify counter-narrative resources to promote acts of social justice. This original empirical knowledge has the capacity to influence university education and expand the narrative resources available to sport and exercise students to talk about disability and improve interactions with disabled people. This article also makes an important methodological contribution by applying an innovative narrative analytical technique to story completion data, as well as advancing practical considerations and challenges guiding story completion design and implementation.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 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".