An interrogation of collegiate student athletes' constructions of health, fitness, and body image
Bibliographic record
Abstract
Collegiate student athletes are faced with unique challenges as they are often forced to negotiate between demanding social, athletic, and academic roles. These competing priorities can put student athletes at greater risk for experiencing physical and psychological health problems than their non-athlete peers. Mounting evidence suggests student athletes are prone to negative consequences such as alcohol abuse, depression, disordered eating, hazing, doping, poor academic performance, and committing sexual violence. Although there exists a large body of research examining student athlete experiences as they pertain to these negative health outcomes, no published research has specifically addressed how student athletes define and conceptualize health. This study explores the ways student-athletes construct health, fitness, and body image using in-depth, semi-structured interviews conducted with 20 actively competing collegiate student athletes. We examined the athletes' understanding of these concepts, as well as how their experiences as student athletes contribute to this understanding. Thematic and discursive analyses were applied to the interview materials influenced by key themes identified in existing literature, themes emerging from interviews, and a constructivist lens. The findings from this study have theoretical and practical applications. With regard to theory, this study can inform further inquiry into how populations conceptualize aspects of health, and how this could manifest into adverse behaviours, such as alcohol abuse or disordered eating. With regard to practice, the findings from this study can be used to inform counseling and wellness practices implemented by sport administrators, such as strategies surrounding mental health.Acknowledgments: SSHRC, McGill University
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".