Identification of intrinsic, interpersonal, and contextual factors influencing disengagement from high performance sport
Bibliographic record
Abstract
A qualitative multiple case study research design was implemented to investigate the experience of disengagement from high performance sport among athletes at different stages of this transitional process. The purpose of this study was to examine athletes' anticipated and actual disengagement experiences. Of particular focus were the intrinsic, interpersonal and contextual factors perceived to influence the disengagement experience. Two current high performance athletes, two athletes in the midst of the disengagement transition and two former athletes volunteered to describe their disengagement experiences in in-depth, audio-taped interviews. Interviews were also conducted with two individuals from the athletes' respective personal and sport communities. An analysis of individual cases as well as a cross-case comparison revealed the presence of intrinsic, interpersonal and contextual factors. Intrinsic factors include Positive Framing; Personal Identity; Post-competitive Career Plans; Competitiveness; Self-Confidence; and Cross-career Competency. Interpersonal factors include the Presence and Quality of Interpersonal Support. Contextual factors include the Quadrennial Cycle; Autonomy of the Disengagement Decision; Achievement of Performance Expectations; Organizational Focus; Educational Status; Concurrent Life Changes; and Employment Barriers. These factors were confirmed and refined through feedback interviews with participants. These findings are discussed in terms of their relationship to and extension of earlier research pertaining to retirement from sport. It is argued that these results support the conceptualisation of disengagement from sport is a complex, multi-faceted experience, influenced by a variety of factors.
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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 | 0.007 | 0.010 |
| 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 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".