Youth sport coaching as social contribution: Exploring developmental pathways to community service
Bibliographic record
Abstract
The concept of Contribution – a thriving individual giving back to their community and society – is posited as the ultimate stage of Positive Youth Development (Lerner, 2005). In youth sport, coaching is a direct example of such “giving back”, whereby former youth sport participants devote their time and energy to providing positive sport experiences for the next generation. Yet pragmatically, recruiting and retaining coaches remains one of the biggest challenges faced by youth sport organizations . This research examines the developmental experiences and pathways by which youth sport participants develop into adults who contribute back to the youth sport community via coaching. This qualitative study used a critical realist Grounded Theory approach (Kempster & Parry, 2015). Semi-structured interviews were conducted with current youth sport coaches who had personally experienced the successful developmental pathway from youth sport athlete to coach, seeking to identify key youth sport experiences, relationships, and program characteristics that facilitated their transitions into coaching. Results indicate a transitional pathway from athlete to coach that is broadly guided by a three-step developmental process: 1) Opportunities to practice leadership and coaching skills as a youth athlete, 2) Engagement in a wider sport community during or after youth sport participation, 3) A personalized invitation to coaching, with positive recognition of an individual's potential to be an effective coach. This research provides insight into tangible steps that organizations can take to increase the likelihood that athletes will contribute back to youth sport through coaching.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".