Negotiating Language Contact and Identity Change in Developing Tibetan-English Bilingualism
Bibliographic record
Abstract
This article explores the identity struggles of a community of Tibetan refugee women in the Indian Himalayas whose educational program combines a traditional Buddhist philosophical curriculum in Tibetan alongside a modern, secular bilingual curriculum in English-Tibetan. Ethnographic and action research data illustrate how negotiations of meanings in multicultural, multilingual EFL/EIL contexts go well beyond mere linguistic features to include cultural and gender identity struggles. Five students serve as case studies to consider five alternative patterns of identity and language negotiations: rejection, assimilation, marginality, bicultural accommodation, and intercultural creativity. The author relates these cross-cultural identity negotiations to various gender identity stances. She concludes by recommending a program of inter-cultural language teaching to address the increasingly global context of English language teaching and learning.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".