Extreme Sport, Identity, and Well-Being: A Case Study and Narrative Approach to Elite Skyrunning
Bibliographic record
Abstract
Although extreme-sport athletes’ experiences have been explored in sport psychology, more research is needed to understand the nuanced identity meanings for these athletes in the context of health and well-being. A case-study approach grounded in narrative inquiry was used to explore identity meanings of 1 elite extreme-sport athlete (i.e., skyrunner Kilian Jornet) in relation to well-being. Data gleaned from 4 documentary films and 10 autobiographical book chapters describing the Summits of My Life project were subjected to a thematic narrative analysis. Two intersecting narratives—discovery and relational—threaded the summits project and were used by Jornet to construct an “ecocentric” identity intertwined with nature in fluid ways, depending on 3 relationships related to well-being: the death of climbing partner Stéphane Brosse, team members’ shared values, and her relationship with partner Emelie Forsberg. An expansion of identity, health, and well-being research on extreme-sport athletes beyond simplistic portrayals of them as pathological risk takers and/or motivated by personality traits was gained from these findings.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 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".