Valuing equality and diversity? An analysis of Asian international students’ experiences at the University of Manitoba
Bibliographic record
Abstract
As a major hosting country of international students, Canada has benefited both socially and economically. Although international students come from diverse backgrounds, the majority are South and East Asians (Crossman, Choi, Lu, & Hou, 2022). Many Asian international students choose Canada to pursue better educational and occupational futures, but along the way, they experience a number of challenges to achieving this goal. Moreover, the COVID-19 pandemic has greatly worsened the economic, social and cultural conditions for many Asian international students. My study is a part of a SSHRC-funded project named “Examining the Racialization of Chinese, Indian and Korean Students in Halifax, Montreal, Toronto, Vancouver and Winnipeg”. As a research assistant in Winnipeg, I have conducted eight interviews with South and East Asian international students to ask about their experiences at the University of Manitoba. This study uses critical race theory to interpret the results. The results of this study reveal that many Asian international students experience difficulties such as low income, cultural shock, and racism. These experiences are partly the result of institutional policies at the university that embed inequality into various aspects of the educational experience. The reduction of services and the lack of networking during the COVID-19 pandemic have further jeopardized Asian international students from reaching their goals. The conclusion of this thesis outlines some policy recommendations for the improvement of Asian international students’ educational experience at the University of Manitoba in the future.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.024 | 0.008 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".