Bringing Anti-Racism into Historical Explanation: The Victoria Chinese Students’ Strike of 1922-3 Revisited
Bibliographic record
Abstract
Anti-racist theory draws attention to the socially constructed and contested nature of racial categories. This paper applies anti-racist theory to a case study of the 1922-3 Chinese students' strike in Victoria, British Columbia, and argues that school segregation was less about which schools students would attend and more about whether racialized Chinese people were part of, or could be part of, the imagined community of Canada as nation. Racialized discourse not only fixed “the Chinese” as outsiders to the imagined community, it also enacted colonialism by naturalizing the Anglo-European occupation of the territory of British Columbia. But there was also a significant group of Canadian-born Chinese in Victoria who had used provincially controlled schools to assimilate to dominant values and gain sufficient cultural capital to directly challenge racialized binaries. This group claimed “Canadianness” in their own right and staunchly resisted segregation. The intervention of Anglo-European anti-racists in the dispute further underlines the socially constructed and contested nature of racial categories. Finally, the more powerful fixing of Chinese as alien in Canada through the 1923 Chinese Immigration Act helps to explain the manner in which the students' strike came to close at the beginning of the 1923-4 school year.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.025 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| 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".