The Youth Olympic Games as a turning point in Turkish athletes’ career transitions
Bibliographic record
Abstract
This study investigates the long-term impact of Youth Olympic Games (YOG) participation on the career transitions of Turkish athletes between 2010 and 2020, a topic that remains underexplored in sport career development literature. Guided by the Athletic Career Transition Model (ACTM) and the Holistic Athletic Career Model (HACM), semi-structured interviews were conducted with eleven former YOG athletes to examine their experiences before, during, and after the Games. Findings revealed four interrelated themes across the pre-, during-, and post-YOG phases. Athletes experienced the shaping and reconfiguration of athletic identity, as YOG participation validated or destabilised their self-perceptions. They faced substantial psychological demands and employed varied coping strategies, navigating pressures, emotional strain, and demonstrating resilience. Participants also had to negotiate life beyond sport, balancing challenging academic responsibilities and social pressures alongside intensive training schedules. Lastly, the YOG served either as a bridge toward sustained elite progression or as a turning point, often leading to burnout and early disengagement. The study highlights the urgent need for athlete-centered support systems, including transparent qualification structures, psychological services, dual-career programs, and sustained financial assistance. These findings underscore that YOG participation, while potentially transformative, must be embedded within robust developmental frameworks to ensure long-term athletic and personal sustainability.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| 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".