The Development of Youth Soccer Coaches: An Examination Within the Unique Coaching Context of Recreational Youth Sport
Bibliographic record
Abstract
The purpose of this research is to explore the context of youth recreational soccer, and to examine how coaches volunteering in this context learn to coach soccer. Framed within Jarvis’ (2006, 2007, 2008, 2009) theory of lifelong learning and employing a mixed-methods approach, this dissertation research had two distinct phases. Phase One involved the collection of data via an on-line survey from 433 recreational youth soccer coaches from Eastern Ontario. The survey served to collect demographic information, as well as general information about their team, their role as a recreational coach, and their approach to learning. The data analysis for the on-line surveys was comprised of an analysis of descriptive statistics. Phase Two involved semi-structured interviews. Recruited through their participation in Phase One, 30 coaches were purposefully targeted and interviewed based on their varied biographies, experiences, and social contexts. Additionally, seven soccer administrators were interviewed. Interview data was analyzed according to the principles of thematic analysis (Braun & Clark, 2006). Findings examine the biographies of youth recreational coaches, their coaching context, how recreational coaches learn to coach, issues of shared responsibilities related to learning, as well as practical implications. It is suggested that recreational coaches differ from one-another on many factors, and that the context of recreational youth soccer is similarly diverse and presents unique challenges to coaches. Recreational youth coaches learn to coach through a variety of sources; mostly through informal learning situations. Responsibilities surrounding coach development fall on the shoulders of individual coaches and clubs, as well as regional, provincial, and national associations; and suggestions for increased engagement in this regard are provided.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".