Bibliographic record
Abstract
Much research has highlighted the potential of sport programming to foster youths life skill (LS) development, yet no similar exploration has focused on emerging adults LS development through their early coaching experiences. Guided by Holt and colleagues (2017) Model of PYD Through Sport, this exploratory qualitative study involved a partnership with a local sport for development (SFD) facility to gain an understanding of coaches experiences and LS development as emerging adults. Eight coaches and/or sport leaders employed at MLSE LaunchPad who identified as emerging adults (Arnett, 2000) engaged in semi-structured interviews with open ended questions framed around PYD through sport, LS development and emerging adulthood. Results emerged through five interconnected themes: (a) developing LS as young athletes, (b) conceptualizing LS at the SFD facility, (c) contrasting LS development in high performance sport and SFD, (d) recommendations for SFD facility, and (e) developing new LS as coaches. Findings offer insight into LS development through sport beyond youth (i.e., into emerging adulthood), in diverse roles (i.e., among coaches versus athletes), and in diverse contexts (i.e., in SFD versus high performance sport). This work is considered in the context of coaches utilizing an implicit and/or explicit approach to LS development (Bean et al., 2018), laying the foundation for extensive future work exploring LS development across the life course, while offering preliminary implications for the SFD facility.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".