Cultural Exclusion and the Transformation of the Cultural Landscape: The Origins of Anti-Chinese Racism in Canada
Bibliographic record
Abstract
Anti-Chinese racism in Canada is a social structure of racialized exclusion that over time came to be built into the settler colonialism that continues to shape the country. Colonizers of European, and especially of British and French origins, have consequently created the cultural landscapes that constitute the country (i.e., its material constructions and dominant cultural overlays). When read against these landscapes, people of Chinese origins and members of other racialized groups continue to be positioned as aliens who do not belong in the country in way in which people racialized as white are not. Focusing on British Columbia (BC), Canada’s westernmost province, and the historical activity of people of Chinese origins, this paper traces the history of anti-Chinese racism and its links to Anglo-Canadian settler colonialism. Canada has long been linked to China, and the Chinese entered BC at the same time as Europeans before the country existed. Despite this, Chinese people have repeatedly been positioned as threats to Anglo-Canadian dominance, and especially to control over the land and its resources. Chinese Canadian resistance to racist exclusions, along with that of other groups, has led to the elimination of legislated exclusions. However, historic exclusions continue to shape cultural landscapes and popular understandings of who belongs and who does not. Remaking these landscapes requires an antiracist project of pursuing common projects that cross over racialized differences to remake the territory in ways that affirm the presence of all the peoples of Canada.
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 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 | 0.003 |
| Science and technology studies | 0.042 | 0.020 |
| Scholarly communication | 0.009 | 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".