Bibliographic record
Abstract
This study aimed to understand the support systems that might better enable canoe-sprint athletes in Japan to win Olympic medals.First, the 12 most successful countries from the results of the past 17 Olympics were identified.Interviews with Japanese canoe officials and coaches suggested that important support factors in those 12 countries included "spirit of athletes," "support staff," "developmental systems," and "information."They also identified Hungary as the world's top country in canoe-sprint competition.In the second phase of this study, interview was conducted with a Hungarian coach of the Canadian team during the World Canoe-Sprint Championships in Canada.These interviews provided information on the support strategies that exist in Hungary, such as the fact that there are many canoe clubs with professional coaches and developmental system.Lastly, the data from a 34-item questionnaire administered to Japanese canoe-sprint experts showed that "acquisition of sponsors," "abundant support funds," "appeal for mass communications," "development of professional coaches," and "organizational support" are important factors in success.The results suggest that strategic management on the part of organization is necessary in Japan.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.059 | 0.007 |
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; both teacher heads agree on what is shown here.
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".