Coach and Athlete Perspectives on Talent Transfer in Paralympic Sport
Bibliographic record
Abstract
Research pertaining to the experiences and motives of Paralympic athletes who transfer between sports is scant. This study aimed to address this gap through semistructured interviews with Canadian Paralympic coaches (n = 35) and athletes (n = 12). Three higher-order themes of "alternative to retirement," "career extension," and "compatibility" were identified. The subthemes of "psychobehavioral" and "physical and physiological" (from the higher-order theme of alternative to retirement) captured reasons leading to transfer, which are similar to reasons athletes may consider retirement. The subthemes of career extension-"better opportunities" and "beneficial outcomes"-shed light on factors that contributed to the withdrawal of negative experiences and reinforcement of positive outcomes associated with transferring sports. Last, compatibility had three subthemes of "resources," "sport-specific," and "communication," which encapsulated factors athletes should consider prior to their transfer. In conclusion, the participants highlighted the importance of transparent and effective communication between athletes and sports to align and establish realistic expectations for everyone involved.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".