The Transnational Politics of Canadian, Chinese-language Television News Production: Media, immigration, and foreign policy
Bibliographic record
Abstract
The complexities and challenges of minority media production bring sharp focus to the sprawling and nebulous politics of transnational migration. By creating news programs meant to inform people with attachments in Canada, Hong Kong, Taiwan, and mainland China, Canadian, Chinese-language television news (CCLTN) workers bring together overlapping political claims from both the Chinese and Canadian states. Each of these governments seek a specific subject-state relationship with Chinese people in Canada and so engages CCLTN production to that affect. My dissertation considers the dilemmas, strategies, and choices of the people charged with creating such news programs by asking the question: how do CCLTN workers navigate the power and influence of the Chinese and Canadian states? I sought answers to my question by interviewing CCLTN workers, including news directors, network presidents, advertising managers, and reporters, in May and June of 2013. Their answers revealed the resourceful ways in which these workers renegotiate the subject-state claims made by each state, even as they are marginalized in their own industry as well as serving communities marginalized by Canada and the PRC. Where the PRC government desires loyal agents through which they can project their power and influence in overseas Chinese communities, CCLTN workers selectively engage by acknowledging the importance of the Chinese state while seeking to develop independent editorial approaches to issues considered to be politically sensitive by the Chinese Communist Party. The Canadian government, by contrast, seeks news coverage which will assist in immigrant adaptation and affirm the efficacy of Canadian multiculturalism. CCLTN workers respond by not only aligning themselves with the goal of immigrant adaptation but also describe the value of their work with respect to cultural retention and minority recognition. In this way, they offer back to the Canadian state a different vision of multicultural practice in Canada.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.023 | 0.011 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".