Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the significance of political and community activism in Toronto’s Chinese Canadian community between 2000 and 2016. Design/methodology/approach Adopting a mixed approach (historical, political and personal), the paper draws from both primary and secondary sources to explore three different cases – SARS in 2003, the Head Tax Redress in 2006 and Maclean’s “Too Asian?” controversy in 2010 – to illustrate discrimination against the Chinese Canadian community in Toronto during the 2000–2016 period while illuminating the importance of safeguarding human rights and dignity in the community. Findings The outbreak of SARS in early 2003 traumatized the whole city of Toronto and sparked waves of racial discrimination and bigotry directed at the Chinese Canadian community. Meanwhile, the community’s ongoing struggle to fight for justice and redress for the Chinese Head Tax seized the opportunity in 2006 to successfully challenge the Canadian government and other political parties to recognize and apologize for the racist tax and its long-term negative impact on the community. However, despite constant efforts, discrimination against Asian Canadians rose again, fueling Maclean’s controversial “Too Asian” article in 2010. Notwithstanding Canada’s positive image abroad, racial discrimination still exists. This paper urges that Canadians of all backgrounds must come together in solidarity and work hard to advocate for social and racial justice and human rights. Originality/value This paper will be of interest to community activists, journalists and scholars who are interested in the history of political and community activism in Toronto since 2000. Policymakers may also learn that an unexpected public crisis like SARS can ignite racial intolerance and negative attitudes toward Chinese Canadian and other communities.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".