Elite athletes' expectations of the Olympic selection process
Bibliographic record
Abstract
Being selected to or de-selected from the Olympic team can disrupt the athletic status quo for elite athletes (Samuel & Tenebaum, 2011). The purpose of this study was to qualitatively examine elite athletes' perceptions of the Olympic team selection process, its impact on their athletic career, and any subsequent transitions that may occur. A sample of two female and five male elite athletes who were attempting to qualify for the 2012 Canadian Olympic team participated in a semi-structured interview prior to the selection process. Data were analyzed using a phenomenological approach (Smith et al., 2011). Analysis of the interviews revealed that athletes who had previous experience with Olympic trials perceived the process as more complex and perceived less support from their sport organization than those who had no prior experience. All athletes believed they would attain their goal of competing at the Olympics, however injury, poor competition conditions, lack of opportunities to make a standard, and poor relationships with sporting bodies were the primary sources of stress and perceived barriers to being selected. Two athletes expected that the outcome of the selection process would determine whether they would transition out of elite sport. The influence of past experiences on athletes' expectations and the complexity of the selection process will be discussed.Acknowledgments: The University of British Columbia Humanities and Social Sciences Grant
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".