Towards the development of a quality youth sport experience measure: Understanding participant and stakeholder perspectives
Bibliographic record
Abstract
Quality sport experiences may be a key underlying mechanism through which continued sport participation may facilitate positive youth development. However, what constitutes a quality sport experience for youth is poorly understood due to a lack of comprehensiveness among existing measures. This study aimed to identify the salient factors that constitute quality sport experience for youth by capturing athletes and stakeholder perspectives with a broader goal of developing a more robust quality sport experiences measure. A total of 53 youth athletes and stakeholders (i.e., parents, coaches, and sport administrators) completed semi-structured interviews or focus groups about what they felt were important aspects of a quality sport experience for youth. Inductive content analysis of the data identified four themes representing important indicators for a quality sport experience for youth: fun and enjoyment, opportunity for sport skill development and progress, social support and sense of belonging, and open and effective communication. These higher order themes were found among each of the groups that have important interpersonal relationships with athletes, as well as among athletes themselves. Each of these themes were also related to one another. Collectively, findings outline a framework to understand what constitutes a quality sport experience for youth. The Quality Sport Experience Framework for Youth will help in the development of a quantitative tool to assess this construct and enable researchers to examine how these experiences contribute to continued engagement in sport and positive developmental outcomes among youth sport participants.
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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 | 0.036 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| 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".