Becoming transnational: exploring multiple identities of students in a Mandarin–English bilingual programme in Canada
Bibliographic record
Abstract
Guided by post-structural perspectives of identities as processes of becoming and transculturation and transnationalism, this study explores how multilingual students in a Mandarin–English bilingual programme form their sense of identities in a dynamic process. Multiple forms of data are collected, including observations, interviews and documents. The findings indicate that multilingual students are mobile, namely, they move across linguistic, cultural and ethnic spaces of interaction. In addition, they challenge the dominant discourse of any fixed and hyphenated identity and take up transcultural and transnational identities that allow their comfortable circulation among different worlds. This study calls for a need to unfold children's multiple and mobile identities and explores new possibilities for life.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.036 | 0.014 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.005 |
| 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".