The Role of Multicultural Media in Connecting Municipal Governments with Ethnocultural and Immigrant Communities: The Case of Ottawa
Bibliographic record
Abstract
This paper aims to advance understanding of the role ethnic and multicultural media can play in connecting municipal governments and Ethnocultural and Immigrant Communities (EICs). Using an innovative mixed-methods approach and methodological triangulation, we compare the access to and use of multicultural media among four EICs—the Chinese, Latin American, Somali, and South Asian—in Ottawa, Canada. Our cross-comparative study yields three main findings: 1) members of participating communities proactively and strategically use a variety of sources to access information about local services; 2) noteworthy differences exist in the access to and use of different types of media both across and within the four EICs, due to demographic and cultural differences; and 3) participants shared challenges and opportunities that multicultural media afford to better connect municipal government and EICs. The paper’s findings make important empirical contributions to the literature on the integrative potential of ethnic and multicultural media by strengthening the reliability of data, validity of findings, and broadening and deepening understanding the role multicultural media play in promoting collaboration between city governments and diverse EICs.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.049 | 0.014 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| 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".