Understanding the meanings created around the aging body and sports by masters athletes through media data
Bibliographic record
Abstract
There is literature based on masters athletes and their involvement in sports at the later stages of \nlife. Masters athletes are exercise-trained individuals who compete in athletic events at a high \nlevel well beyond a typical retirement age (Tanaka & Seals, 2008). These athletes vary widely in \nage but are typically older than 35 years, with many more over the ages of 50 and well into old \nage. The research questions guiding this study included; (a) what are the media representation of \nmasters athletes, and how are they used to generate meanings around aging, sports and the aging \nbody and (b) what are the implications of these meanings on how the aging body is represented \nto the audience. A qualitative (i.e., case study) approach was used to explore what meanings \nwere generated around aging and sports through media narratives in relation to aging \nsuccessfully. Media data in the form of sports magazines (i.e., Runner’s World and Lexis-Nexis \ndata base) were compiled for the data analysis. This research focused specifically on two cases, \n81year old Ed Whitlock, a Canadian long distance marathon runner, and 77 year-old Jeanne \nDaprano, an American masters track and field athlete. The data included (n=41 Ed Whitlock, n= \n17 Jeanne Daprano). The data were analyzed via an inductive thematic analysis (see Braun & \nClarke, 2006). \nThe following central themes emerged a) life-long involvement in sports (higher order themes: \nearlier sporting experience, triumphant return, uninterrupted engagement), (b) performance \nnarratives (serious contenders, reasoning for performance, systematic training, an individualized \napproach), and (c) decline narratives (resistance to declines in old age, sports related injuries, \nmaintenance of performance). This study highlights how both athletes were depicted in the \nmedia narratives, demonstrating that their involvement in sports in later life provided an alternate \nway to view the aging process. The findings from this study seek to extend the understanding of \nmasters athletes, by contextualization how they challenge some of the decline narratives \nassociated with old age.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".