Canadian ethnic media and social capital development : Examining the relationship between broadcasting policy, multicultural programming and sociocultural integration and cohesion in Canada
Bibliographic record
Abstract
Using Canada as a case for analysis, this research investigates the potential for ethnic media, which are mandated to deliver content directed to "racially and culturally distinct" (CRTC, 1999) groups that are not English, French or Aboriginal, to act as an integrative tool for allophone communities, and to stimulate intercultural exchanges amongst all Canadians that can lead to the development of social capital. Given Canada's extraordinary demographic heterogeneity, the mechanisms in place to encourage the development of networks between and among ethnic communities are increasingly important for supporting social solidarity in the broader population (Putnam, 2006). Canada's Broadcasting Act, §3(1)(d)(iii) (1991) and related policies which the Act initiates, including the Ethnic Broadcasting Policy, provide a policy framework for the creation and distribution of culturally and linguistically diverse content" to Canadian audiences, demonstrating official support for the potential social benefits associated with the national availability of ethnic media. By developing culturally and linguistically diverse content aligned with the demographic realities of the Canadian population within a supportive policy environment, ethnic media can provide, an important platform for sharing information and ideas across vast geographic or sociocultural divides, as well as a venue for fostering community building, civic involvement and an active dialogue amongst Canadians of all backgrounds. This research seeks to explore and develop theoretical linkages between the existing policy framework governing ethnic broadcasting in Canada, the broadcasting sector's methods of compliance with existing regulation, and the development of social capital.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| 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".