Dilemma and Strategies of Bilingual Education in A Ethnolinguistically Diverse Region
Bibliographic record
Abstract
The right of learning and using one’s own mother tongue and a second language is integrated into China’s education policies. Therefore, bilingual education is particularly important to protect the rights of ethnic minority students through language policy planning and teaching. Due to the special sociolinguistic situation in Bayin’golin Mongolian Autonomous Prefecture in Xinjiang Uyghur Autonomous Region that Chinese, Mongolian and Uyghur are all official languages and Chinese is the lingua franca for ethnic minority groups, it is vital to promote bilingual education for Mongol students. This paper looks at bilingual education for Mongols in Xinjiang based on a case study of Xinjiang Bazhou Mongolian High School in Korla, the capital city of Bayin’golin Mongolian Autonomous Prefecture. This case study describes the implementation of a specific bilingual education model and the challenges of bilingual education in this real-life school teaching. It also outlines the strategies and recommendations to improve bilingual education at Xinjiang Bazhou Mongolian High School, with implications for schools in other areas.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.013 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| 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".