Countermeasures of Chinese Women Ice Hockey Being Downgraded at the World Championship with the Difference from European
Bibliographic record
Abstract
with the unbalanced development of world women ice hockey,American and Canadian are more skillful than others,but Chinese met with a downgrading at two successive world championships.There is a strong contrast between Chinese current situation and international development.With the methods of documental information,video observation,competitive data collection and comparative analysis,the paper objectively analyzes Chinese competitiveness basing on their performance and in comparison with European teams at the 2011 women ice hockey world championship.It indicates the factors of influencing Chinese development relate to physical quality,specialized quality,Chinese current situation,European and American system of league matches,Chinese training ideas and development of core players.It suggests some countermeasures as follows: starting at actual competition to compete for training,reforming the system of league matches to enhance the juvenile training,reinforcing the technical and tactical details,having a training of shooting ability.Its purpose is to find out the difference between Chinese and European teams,and provide a reference for improving Chinese ice hockey.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".