Understanding Chinese International Students' Struggle in Canadian University during COVID-19: A Literature Review
Bibliographic record
Abstract
The economic impact of international students in Canada is tremendous. As the enrollment of domestic students has decreased, the admission of overseas students has made up for the financial losses that Canadian institutions suffer due to the drop in domestic student enrollment. China is a significant exporter of international students to Canada, sending a sizable number of them there yearly. Chinese international students' entrance to Canadian universities is being impacted by the COVID-19 pandemic. This article contends that because of their temporary immigration status, international students in Canada are at risk. It does this by drawing on the literature analysis approach. They are not included in the majority of government assistance initiatives intended to assist Canadians during this outbreak. The majority of overseas students struggle financially and psychologically as a result of the pandemic. The circumstance is causing a further drop in the admittance of international students, with economic repercussions for Canadian institutions. The report advances our knowledge of the struggles faced by international students and educational institutions during the COVID-19 pandemic by examining the issues they face as well as the methods needed to increase their resilience and universities' capacity.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".