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 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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.043 | 0.015 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".