Bibliographic record
Abstract
The purposes of this study were 1) to clarify what Paralympic movement was, 2) to\ndescribe activities conducted in the Women in Sport Committee (WISC) of the International\nParalympic Committee (IPC) along with international women and sport movement, and 3) to\nsuggest strategies which Japan should initiate towards new Paralympic and women in sport\nmovement in future.\nParalympic Games is the highest level of adapted sport games in terms of pursuit excellence.\nIn addition, Paralympic Movement is all activities to achieve the vision of the IPC,\nwhich is “ - To Enable Paralympic Athletes to Achieve Sporting Excellence and Inspire and\nExcite the World.”\nAfter the agreement of the IPC and International Olympic Committee (IOC) Co-operation\nhas taken in October 2000, the relationship between IPC and IOC has been accelerated. One of\nthe examples of the agreements indicates that the organizing committee must operate not\nonly Olympic Games but also Paralympic Games. Consequently, a new trend of merging the\nOlympic Committee and the Paralympic Committee at the national level has occurred, such as\nNetherlands Olympic Committee in 2008.\nWomen in Sport Movement have been active since 1994 First World Conference on Women\nand Sport at Brighton, England. IPC WISC has been also taking strong initiative to advance\nthe situation of women in sport leadership for female athletes with disabilities. Particularly,\nIPC produced the Women in Sport Leadership Toolkit by modifying the Montreal Toolkit\nwhich was a product of the 2002 Second World Conference on Women and Sport. And, the\nWomen in Sport Leadership Toolkit is expected to be a useful guideline for each country.\nIn Japan, a big gap exists between Japanese Olympic Committee and Japanese Paralympic\nCommittee due to different governmental backgrounds and structures. In conclusion, the\nresults suggested that Japan needed to be more aware of the trend of the co-operation\nbetween the IOC and IPC, and consider effective strategies to deal with this new trend.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.018 |
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".