Understanding the meanings created around the aging body and sports through media representations of elite masters athletes
Bibliographic record
Abstract
Masters athletes compete in athletic events at the elite level after the point when most elite athletes retire. These athletes typically begin this stage of their competition careers between 30 and 40 years and continue in this journey in some cases to the age of 90 or older. The purpose of the present study was to explore media representations of such athletes to extend understandings on the portrayal of ageing, the older body and sport and the potential impact on understandings of ageing and sport participation. The athletes focused on were 81 year old Ed Whitlock, a Canadian marathon runner, and 77 year-old Jeanne Daprano, an American track and field athlete. Both athletes were the best athletes in their age group category based on their international accomplishments as runners. Media representation(s) (i.e. newspapers, articles in Runner’s World magazine) of both athletes (n = 41 Whitlock, n = 17 Daprano) were collected and analysed through an interpretive thematic analysis. Two higher-order themes were identified: (a) discovery and rediscovery of sports and competition – which culminated into ‘ageing into sport’ and (b) performing in a declining body – which culminated into ‘ageing out of sport’. These findings extend the literature on masters athletes, demonstrating how media stories of two prominent athletes’ identities circulating at the broader cultural level (re)creates particular meanings around ageing and athletics that can simultaneously encourage and discourage sport participation.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".