Bibliographic record
Abstract
Athlete satisfaction is often a direct result of coaching behaviours (Iso-Ahola & Hatfield, 1986). Effective coaches adapt to various antecedents such as level of competition, age, gender, and ability of athletes; there is not a 'one size fits all' model of coaching (Cushion, 2010). Although coaching science research has focused on many different levels of competition, one area that has received scant attention is coaches' of masters swimmers. This is important since only 15% of Canadian adults meet the current Canadian exercise guidelines (Stats Canada, 2013) and 75% of seniors are physically inactive (Warburton, Ashe, Miller, Shi, & Marra, 2009). Although athlete motivation is determined largely by their own beliefs, thoughts, and values, coaches represent an important motivational factor (Deci & Ryan, 2002). The purpose of this study was to explore masters swimmers experiences of coaching. In particular, this study examined the journey of masters swimmers in sport and identified the various coaching characteristics and behaviours that they felt promoted ideal training and competition environments that led to improved social, health, and performance outcomes. Qualitative descriptive methodology was used to guide the current analysis and Braun and Clarke's (2006) guidelines of thematic analysis were used for identifying, analyzing, and reporting themes within the data. Results revealed three themes which were called master athlete evolution, coaching knowledge and behaviours and outcomes. Despite the differences in career progression and experience of all the swimmers, several common coaching preferences emerged. These coaches established environments where the skills and values taught from their sport were promoted and encouraged in both sport and in life. Creating these positive environments was not about what the coaches did, but rather how they did it. The current coaches fostered environments that provided their athletes with positive social, health, and performance outcomes. This was accomplished through the coaches' influence on their athletes' motivation through their communication, organization, and teaching. Overall, these findings have provided a greater understanding of the preferred coaching behaviours of masters swimmers. Future studies investigating the influence of coaching on masters athletes or the coaching preferences of masters athletes may use these findings to advance research in this domain.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".