Legal Discrimination against the Chinese in Canada: The Historical Framework
Bibliographic record
Abstract
Professor Constance Backhouse narrates the experience of Chinese Canadian Lem Wong to show the impact of historical discrimination against Chinese immigrants. Wong's settlement in Canada was costly, given the ballooning Chinese Head Tax. His business opportunities were effectively limited to laundries or restaurants, due to a racist job market and discriminatory legislation. Legal barriers to interracial marriage and an expensive and complicated immigration system separated Wong from his family in China for decades. Lem Wong's business was potentially infringed by the White Women's Labour Law, which prevented Chinese men from employing white women. Despite the many systemic barriers to the Wong family's social and economic integration, many of Lem Wong's children became highly successful Chinese Canadian professionals. It is problematic to construct Lem Wong's experience as part of a “grand Canadian narrative” told to garner national pride. It is a story that must be told with full consideration of the many racist legal and social barriers Canadians erected for Chinese newcomers.
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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 | 0.003 | 0.006 |
| Science and technology studies | 0.048 | 0.020 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".