Learning to orient toward Myanmar: ethnic Chinese students from Myanmar at a university in China
Bibliographic record
Abstract
Based on a larger ethnography (Li, 2017. Social Reproduction and Migrant Education: A Critical Sociolinguistic Ethnography of Burmese Students’ Learning Experiences at a Border High School in China. (PhD), Macquarie University. http://www.languageonthemove.com/wp-content/uploads/2017/05/LI_Jia_Social_reproduction_and_migrant_education.pdf) and focusing on 14 international students from Myanmar but of Yunnan origin, this paper aims to offer a nuanced account of their perspectives, learning experiences and trajectories during their Putonghua-medium degree programs at a Chinese university, and to shed light on the complex interplay of language, culture and state that international students experience in China and beyond. Informed by the concepts of linguistic nationalism and banal nationalism, the study examines how, while many of them had self-identified as ‘Chinese’ and aspired to study in their imagined ancestral homeland, their lack of legitimate forms of speaking and writing Putonghua and Chinese citizenship challenged their sense of authentic Chineseness and negatively impacted their academic attainment. We also analyse how the university essentialised Myanmar cultural and linguistic practices, and gradually oriented them to identify Myanmar as their (f)actual ‘homeland’ instead. We argue that the PRC government values other national languages as resources in global market and takes a reciprocal approach in promoting Putonghua. However, complicated by linguistic and cultural essentialisation in discourse and practice, this approach in effect may reproduce the linguistic hierarchy between standard/ national language(s) and other linguistic varieties already exists in China and beyond.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".