“Sitting with myself by myself”: Indian students in Canada during the pandemic
Bibliographic record
Abstract
The number of international students from India in Canada has increased rapidly in the last five years. Students from India now comprise 34 percent of Canada’s international students. This article places the remarkable growth of Indian international students within the broader context of Canada’s internationalization of higher education. Drawing from a national survey, qualitative interviews, and secondary data, it examines the changing profile of Indian international students and the major trends and challenges experienced by Indian international students in Canada during COVID-19. The paper identifies a recent trend of “vocationalization” of Indian international students and several associated vulnerabilities due to the increasing commercialization of international education. Our findings also point to the complex intersections of psychosocial, academic, and economic disruptions during the pandemic, exacerbating the precarious position of Indian international students.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.049 | 0.014 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.004 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".