Towards sustainable internationalization in post-COVID higher education: Voices from non-native English-speaking international students in Canada
Bibliographic record
Abstract
International students have been a dominant topic in Canadian government and institutional strategies in recent years (Tamtik, 2017; Trilokekar & El Masri, 2020). As of 2019, the Canadian Bureau of International Education (CBIE) reports over 600,000 international students in Canada across all levels of study. In the midst of the COVID-19 pandemic, the complexities around student engagement, learning and community building are complicated by remote learning. International students, in particular, face increasing challenges due to isolation from home countries and a reduction of in-person support services. We must now, more than ever, identify and address the lack of supports available to international students. This qualitative study provides voices from non-native English-speaking international students in Ontario universities speaking about the institutional support systems they have experienced in Canada. The findings are reported in a narrative format.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".