Bibliographic record
Abstract
This book explores how the recruitment and retention of Asian international students in Canadian universities intersects with other institutional priorities. Responding to the growing need for new insights and perspectives on the institutional mechanisms adopted by Canadian universities to support Asian international students in their academic and social integration to university life, it crucially examines the challenges at the intersection of two institutional priorities: internationalization and anti-racism. This is especially important for the Asian international student group, who are known to experience invisible forms of discrimination and differential treatment in Canadian post-secondary education institutions. The authors present new conceptualisations and theoretical perspectives on topics including international students’ experiences and understandings of race and racism, comparisons with domestic students and/or non-Asian students, institutional discourse and narratives on Asian international students, comparison with other university priorities, cross-national comparisons, best practices, and recent developments linked to the COVID-19 pandemic. Foregrounding the institutional strategies of Canadian universities, as opposed to student experience exclusively, this direct examination of institutional responses and initiatives draws out similarities and differences across the country, compares them within the broader array of university priorities, and ultimately offers the opportunity for Canadian universities to learn from each other in improving the integration of Asian international students and others to their student body. It will appeal to teacher-scholars, researchers and educators with interested in higher education, international education and race and ethnic studies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.783 | 0.646 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".