A longitudinal interpretative phenomenological analysis study of athletes' lived experiences in elite disc golf competitions
Bibliographic record
Abstract
Gaining the inside perspective of an elite athlete throughout the competitive season provides a unique approach to understand the lived experience during multiple competitive events. The purpose of the present study was to investigate how elite disc golf athletes perceive and interpret their experiences of performing during various training and competitive events over the course of an elite disc golf season. Two elite disc golf athletes, one man and one woman, were recruited using homogeneous purposive sampling. The participants were interviewed three times and observed during three competitive events, as well as before and after a training session. A longitudinal interpretative phenomenological analysis (LIPA) was adopted to capture temporal and dynamic changes of the participants' lived experiences. The findings illustrated the athletes' personal experiences of performing during competitive disc golf events, with both athletes' experiences of competition changing during the season. Their competitive experiences appear to relate to the meaning disc golf has for the athletes, which in this study had both an experiential and existential level of meaning over time. Such a finding illustrates the importance of honoring athletes' unique experiences in making sense of their performances during an elite disc golf season. Taking the time to understand athletes' perceptions of their personal experiences appear important in attempting to understand their sense-making of their hot cognition before, during, and after competitions.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| 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".