Racism Against Japanese Canadians in British Columbia: My Reflections on Racism Inspired by John Holt
Bibliographic record
Abstract
Racism against Japanese Canadians in British Columbia (B.C.) has been an ongoing issue with its roots ingrained in the past. The province of B.C. has a history of putting Japanese Canadians into internment camps during World War II due to their ethnic background and are still refusing to include this tragedy into the current B.C. curriculum. This reflective autoethnography guided by John Holt’s Learning All the Time, explores the history and current issues that Japanese Canadians face in B.C. Through the lens of the researcher’s own experiences with racism, the issues of being a “model minority”, the difficulties of cultural identity, and the current state of racism towards Asian Canadians are discussed. The study concludes that, the lack of historical recognition from the government and with the rise in hate crimes towards Asian Canadians due to COVID-19, racism towards “model minorities” is very much alive in today’s society.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.075 | 0.018 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.011 |
| 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".