Studies to Bilingual Education of Chinese University Undergraduate Course
Bibliographic record
Abstract
After China joined WTO, foreign exchange is frequent day by day, international competition is intense day by day, social need's talented person not only have to be skilled in respective research area, moreover must be able to carry on wide-ranging international communication, therefore, urgent needs to raise high quality talented person who both are skilled on specialized knowledge and understands foreign language. Bilingual education is that advancement higher education internationalization, it is also powerful action that advancement college education reform, it is also inevitable product that contemporary society internationalization, it is choice inevitably that China and world connection. Implement bilingual education will further enhance Chinese student's international competitiveness. Develops bilingual education is inevitable trend that Chinese higher education reform development. This article take Management bilingual education as an example, it has researched to bilingual education development in Chinese University, it has analyzed Chinese University bilingual education present situation and question, and it analysis reasonable disposition question about curriculum, teaching material and teaching object, and it has made detailed discussion on bilingual educational model, bilingual education course content and bilingual teaching method reform and so on. Key words: Higher Education; Special Course; Bilingual Education; Teaching Method; Educational Model
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".