Perceptions, motivations, and pressures of contribution for Canadian Olympic athletes
Bibliographic record
Abstract
Olympic athletes figure prominently on the world stage and some have used their spotlight to raise awareness on a number of social issues (e.g., Clara Hughes’ work on raising mental health awareness). Studies examining high level sport have found that teams and athletes donate their time and resources for a combination of altruistic and self-serving reasons, in practices known as corporate social responsibility or strategic philanthropy. However, no such studies have specifically examined the precise nature of how Olympic athletes contribute, how they feel about their contributions, or why they contribute in the ways they do. The current study represents an exploratory study examining the perceptions, motivations, and pressures of contribution experienced by Canadian Olympic athletes. Semi-structured interviews were conducted with two Canadian Olympians and revealed how the athletes contributed to themselves, their communities, and their sport for both altruistic (e.g., personal values, helping the next generation, or a connection to a group) as well as for self-serving reasons (e.g., obtaining access to facilities, improving future funding applications). Additionally, the Olympians felt both moral (e.g., wanting to improve the sport) and social (e.g., helping those that have helped them) pressures to contribute as a result of their success as athletes. The athletes also described scheduling, personal finances, and the bureaucracy of their national sport organization as barriers that limited their ability to contribute. The findings of this study improve our understanding of Olympic athlete contribution, provide direction for future research, and offer insights for coaches and sport psychology professionals seeking to help athletes achieve greater satisfaction with their Olympic experience. Keywords: 5Cs model, gratitude, citizenship, corporate social responsibility
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".