A Study of Mental Toughness (MT) and Aquatic Sport Coach Education in Four Countries
Bibliographic record
Abstract
MT has been identified as an important component of elite athletes’ success (Bull et al., 2005; Gould et al., 2002; Jones et al., 2002; Middleton et al., 2004; and Orlick, 1998). MT was defined by Jones (2002) as “… having the natural or developed psychological edge that enables you to, generally, cope better than your opponents with the many demands (competition, training, lifestyle) that sport places on a performer, and, specifically, be more consistent and better than your opponents in remaining determined, focused, confident, and in control under pressure .” This study examined the extent to which MT is included in coach education programs in four top performing countries (Australia, Canada, Great Britain, the United States) in aquatic sports (diving, swimming, synchronized swimming, and water polo) at the summer Olympic Games. An open access web based research method was used to examine coach education program curricula provided by National Sporting Organizations (NSO) of the countries and sports in question. The presence of MT was evaluated by assessing which of Jones’ (2002) identified MT attributes were contained in the coach education programs. Analysis showed Australia and Great Britain’s MT components most closely align with Jones’ characteristics, followed by Canada and the United States. Despite the lack of MT components in USA aquatic sport coach education programs, their performance at the past four summer Olympic Games put them at the top of the aquatic sports medal count. Further studies should be conducted to explain the effect of coach education programs and the inclusion and exclusion of MT attributes on Olympic Game performance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".