On Connotative Development of Foreign Language Teaching in Chinese Universities
Bibliographic record
Abstract
This thesis studies connotative development of foreign language teaching in universities in China, and commits further analysis of the implication of the university education connotative development, illustrates three stages of evolution of the university education connotative development; it states that university education connotative development advocates the principle of self development. It also analyses current situation of foreign languages teaching in colleges and universities, China has a good foundation for the construction of a global country, to realize its internationalization and modernization connotative development of foreign language teaching in universities in China becomes more important than before. The demand conditions of foreign language talents in China makes the students should understand the western advanced civilization achievements, broaden their horizon, extend knowledge, set up the international consciousness through learning English, so as to promote international communication; the reform of the original mode and the building of a new English professional talent training mode is what society call for. Furthermore, it constructs connotative development mode of foreign language teaching in universities, university education values in training talents that adapt to the new era of social development, and then promote the development of social productive forces. The thesis sums up that the research results and then puts forward the essence of connotative development of universities in China.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".