Reflection on education equity in Vietnam: Teachers' and students' voices in an English tourism programme
Bibliographic record
Abstract
Abstract In this article context, I recall my memories as a Vietnamese English for Tourism Purposes (ETP) programme teacher and a student who grappled with many inequities in the nationwide process of internationalization of higher education. The equity-related issues include the teacher's unpreparedness with the adoption of foreign curriculum, the teacher's lack of recognition of the local cultures, and the unfair treatment of the Vietnamese ETP interns in the workplace. I write this article in the role of a narrator, sharing my personal and professional experiences to give the status quo of ETP education in Vietnam and the various nuances that help unpack the realities of this situation. This reflective article intends to picture the inequities in Vietnamese higher education internationalization that both Vietnamese students and teachers encounter and to pave the road for further discussions to construct future scholarship and research.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.018 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.014 |
| 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".