Elite athletes' experiences with an Olympic team selection process: Coping, appraisals, and goals
Bibliographic record
Abstract
Despite having implications for elite athletes’ careers and overall well-being, there is a dearth of research examining high-performance team selection processes. The purpose of this study was to explore seven elite athletes’ experiences with the 2012 Canadian Olympic team selection process and its impact on their athletic careers from an interpretative phenomenological analysis perspective (Smith et al., 2009). Participants took part in three semi-structured interviews prior to or during the Olympic team selection process, once the Olympic team was announced, and after the Olympic Games. Six athletes were not selected while one athlete competed in the 2012 Olympic Games. Analysis of the interviews revealed that participants organized their athletic and education/work endeavours around their goal of being selected to compete in the Olympic Games, demonstrating significant investment and sacrifice. Yet upon non-selection, participants used cognitive reappraisal as a strategy to cope with the selection outcome and to assist in disengaging from their 2012 Olympic goal. While the participants’ focus had primarily been on being selected to the Olympic team, they reengaged with new and meaningful athletic goals after failing to achieve their desired performances in qualification phases. For example, three of the participants who were not selected stated that they wanted to transition to a new event within their sport the following year. The influence of goal reengagement and reappraisal after the selection process on perceptions of goal progress will be discussed within the context of participants’ stages of athletic career.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".