Chinese International Secondary Students’ Experiences with Racism: “It Was the Same Before and After COVID… It Was Just Something Really Normal.”
Bibliographic record
Abstract
The number of international students enrolled in Canadian K-12 schools has grown tremendously, but there remains limited research available that provides insights into the unique perspectives and challenges of this population. Through in-depth interviews with five Chinese international secondary school students and using Critical Race Theory (CRT), neo-racism and Asian Critical Theory (AsianCrit), this study identifies four key themes that help explore their experiences during the COVID-19 period with anti-Asian sentiments and racism in GTA schools. The article highlights both the strengths and limitations of CRT and AsianCrit and the contributions of Neo-racism in fully accounting for the racist experiences of Chinese international secondary students. It suggests the importance of exploring newer frames such as neo-racism, but also co-ethnic racism and new geopolitics to analyze what shapes and defines international students’ experiences. Finally, the article stresses the need for K-12 schools to confront their problematic institutional cultures and make a sincere and concerted effort to establish an inclusive and supportive environment for 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".