A holistic understanding of PYD in sport: The consideration of developmental context and time
Bibliographic record
Abstract
Despite the flourishing body of literature on young athletes' personal development through sport, there a remains a lack of consensus on how to conceptualize and measure positive youth development (PYD). Indeed, youth sport programs can vary considerably in terms of their goals, structure, and consequently, in youth's sport experiences. It can also be argued that youth sport programs can help to facilitate PYD in many different ways; for example, equivocal evidence exists supporting both the implicit and explicit approaches to the transfer of life skills learned in sport (Turnnidge, Hancock, & Côté, 2014). The diverse nature of youth sport therefore calls for a developmental context that conceptualizes PYD as the interaction of three key elements: personal engagement in activities, quality relationships, and appropriate settings. This presentation will focus on the consideration of developmental context across time by reviewing findings from four studies of a community youth basketball program of approximately 500 boys and girls aged 8-14. These studies incorporate both quantitative (e.g., systematic observation) and qualitative (e.g., ethnography) methodologies, and collectively suggest that the mechanisms through which PYD occurs is dependent on the nature of a given developmental context. In addition, the specific PYD outcomes resulting from sport participation can be conceptualized on multiple timescales, and are again contingent on the developmental context in which sport take place. These concepts will be situated within the Personal Assets Framework for Sport (Côté, Turnnidge, & Vierimaa, in press), and implications for future research and practice in youth sport will be presented.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".