Contagious Minorities: Chinese Canadians during the COVID-19 Pandemic
Bibliographic record
Abstract
During the COVID-19 pandemic, Canada has witnessed a sharp increase in racial violence against Chinese Canadians, and, in an undifferentiated racism, other Asian Canadians have been seen as bearers of disease as well, which often made them targets of racism. The quick transformation of Asian minority groups into threats of contagion during the pandemic points to the persistence of latent fears and anxieties about Chinese Canadians across generational differences, immigration status, and national origin. This essay reflects on how knowledges about early Chinese newcomers that were generated by colonial administrators laid the foundations for modes of racial governance that continue to inform public policy and public discourse in multicultural Canada in ways at once familiar and new. It examines the 1885 Report of the Royal Commission on Chinese Immigration as an important tool in reinforcing the political goal of “white Canada” by strengthening the power of European colonists. Less than a century later, in 1967, the immigration points system was introduced, preceding the adoption of multiculturalism policy in 1971, both breaking with explicitly racist national policies. Yet there is more continuity than there are differences across the 1885 Report and the 1967 immigration policy. Both participate in a historical narrative that excludes the Chinese from national imagining, laying fertile ground for contemporary anti-Chinese racisms during the recent COVID-19 pandemic. Contemporary media narratives during the pandemic reproduce the same racial hierarchies, excluding Chinese Canadians from the nation. By placing the rise in anti-Asian racism during the COVID-19 pandemic in the long historical trajectory of institutional racism in Canada, this essay argues for the need to learn about the historical legacies of racism to be able to intervene in structural racism so that Canada’s promise of multiculturalism can be grounded in justice and equity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".