No longer ‘the other’: A reflection on diversity in Canadian fiction television
Bibliographic record
Abstract
Canada has played a leadership role in the development of multiculturalism and its use in ethnic and minority television broadcasting as an integrative tool for cultural and racial constituency groups. Canada has mainly opted to emphasize private ethnic broadcasting as the means by which to integrate minorities, along with the support of the public broadcasters’ progressive initiatives. After historically differentiating and framing ethnic/multicultural research and programming initiatives in Canada, this article identifies some lessons and best practices that have emerged from this experience. Using policy analysis from a historical perspective, the authors analyse the enabling mechanisms and strengths, as well as the obstacles and failures that have been experienced in an effort to build an integrated, cohesive and transformative television system in which all members of society are recognized as having a right to both fair portrayal practices and employment opportunities.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.088 | 0.046 |
| Scholarly communication | 0.020 | 0.007 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.007 | 0.015 |
| 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".