Bibliographic record
Abstract
In the process of globalization, each country culture retains an independence from the others besides in reality a fusion of several cultures. Bilingual education as an effective means and intangible resource, which have long been neglected, will play an important part in social and economic development in China.Bilingual education, in this method of language instruction, the regular school curriculum is taught through the medium of a foreign/second language. The foreign/second language is the vehicle for content instruction. The subject of the instruction is to make students master language as well as subject knowledge.This thesis attempts to expound the necessity of the implementation of bilingual education in China in the process of globalization. Bilingual education is mot a unitary language phenomenon and usually displays an essentially economic concern for the languages to be used. Hence, economics can be of service and offer insights and information in the study of language issues that other approaches do not provide so far. besides, the problems in China’s bilingual education are analyzed, followed by a list of suggestions for reference, however, due to a variety of reasons ,there still exist several drawbacks like lack of linear research and whatnot. Those are to be dealt with in further researches.Keywords: Globalization, Bilingual education, Economics, Problems
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".