Psychosocial development through masters sport: What can be gained from youth sport models?
Bibliographic record
Abstract
Sport is primarily the domain of youth and there is a prevailing view that development primarily occurs in youth/adolescence. Although researchers examining human development have typically focused on youth populations, development occurs across the lifespan. Therefore, given the extensive research and theories on youth sport, this qualitative study aimed to utilize these frameworks in the context of Masters sport to determine the potential for developmental benefits (or psychosocial assets) of sport participation across the lifespan. We interviewed 14 adults (nine men and five women) aged 46-61 years (M=50) involved in Masters sport (swimming, running, cycling, triathlon, dragon boating, volleyball, ice hockey, and triathlon). They ranged in skill, competitive, and commitment levels, and were recruited from urban (population 2.5 million) and rural (population approximately 18, 500) areas in Southern Ontario, Canada. Key themes based on the psychosocial outcomes of their sport involvement were: Competence and Confidence; Character; Commitment; Connection; and Cognitive development. Established frameworks from research on positive youth development, particularly Lerner’s 5 C’s model, were used to interpret the findings. Similarly, Developmental Assets (Benson, 1990) were found among the Masters athletes, but these assets held different meaning in mid-later life compared to youth and some developmental areas were no longer relevant in later life (e.g., school dropout, career trajectories). Applying available frameworks from youth sport research to the Masters sport context is useful because it supports the modification of these models and highlights their potential in identifying developmental outcomes of sport participation across the lifespan.Acknowledgments: York University Faculty of Health
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".