Political Communication in A Multicultural Metropolis: Chinese Ethnic Media and the 2023 Toronto Mayoral By-Election
Bibliographic record
Abstract
Chinese are the second largest visible minority group in Canada and the most frequently reported ethnic or cultural origin in Toronto. Mandarin and Cantonese are, respectively, the largest and third largest non-official languages in Toronto. However, little research exists on the role of the Chinese ethnic community in Toronto municipal politics, especially the role of Chinese ethnic media in Toronto municipal elections.\nThe key argument of this thesis is that “Chinese ethnic media represent complementary public sphere(s) for informing and engaging Chinese Canadians in local political participation and discussion.” Through the 2023 Toronto Mayoral By-Election case study, this thesis examines how Chinese ethnic media represent an essential complementary public sphere for informing and engaging Chinese Canadian residents. The author tries to answer these questions: What role do Chinese ethnic media play in Canadian municipal politics? How do Chinese ethnic media cover municipal election campaigns? Are there any similarities and differences in the news reporting of Chinese ethnic media with different origins?\nThis thesis applies quantitative content analysis to examine the “frequency” and “intensity” of election-focused stories, applies qualitative content analysis to explore the “direction” of television and radio programs, and applies qualitative framing analysis to examine the communicators, texts, receivers, and cultures of commentary articles during the campaign period of the 2023 Toronto Mayoral By-Election (April - July 2023). 11 Chinese ethnic media agencies, including dushi.ca, Ming Pai Daily News, Ming Sheng Bao, info.51.ca, Epoch Times, Toronto News Net, Fairchild Television, Talentvision, A1 Chinese Radio, and The Chaser News, are examined in this thesis. Overall, 196 news articles, 10 interviews, and 9 commentary articles are covered in this thesis.\nThe key argument that “Chinese ethnic media represent complementary public sphere(s) for informing and engaging Chinese Canadians in local political participation and discussion” is proven to be established. Chinese ethnic media play an essential role in political communication. They share many similarities with mainstream media and among themselves, especially in news reporting on policy issues, and contribute to the “civic assimilation” of Chinese communities. Meanwhile, different Chinese ethnic media producers show distinct characteristics in the multi-ethnic public sphere due to their various media activism and advocacy in ethnic media structures.\nOther main findings include: (1) Although Chinese ethnic media pay attention to community-specific issues, they focus on diasporic politics related to the PRC government rather than identity politics here in Canada. (2) In most cases, Chinese ethnic media reported Olivia Chow significantly more than any other mayoral candidate, indicating that Chinese ethnic media are more inclined to focus on Chinese Canadian politicians. (3) Most Chinese ethnic media depicted Olivia Chow's identity primarily as “Chinese Canadian” rather than a more limited term such as “Hongkonger Canadian” or a more extensive term such as “Asian Canadian.” (4) Hongkonger-oriented Chinese ethnic media paid more attention to Olivia Chow’s Hong Kong origin and her past story.\n(5) Mainlander-oriented Chinese ethnic media paid more attention to other ethnic Chinese candidates (most of them have mainland Chinese origin). (6) With various formats and exclusive interviews, generally speaking, Hongkonger-oriented Chinese ethnic media performed better than Mainlander-oriented Chinese ethnic media regarding breadth and depth.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".