No one is safe until everyone is safe: Direction régionale de santé publique de Montréal’s risk-based approach to multilingual crisis communication
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Canada’s multiculturalism is situated within a bilingual framework that often restricts Canada’s linguistic diversity, which goes beyond its official languages. The limitations of this framework were exposed by the COVID-19 pandemic, during which government-led crisis communication strategies were guided by the country’s multilingual reality and the risks associated with ignoring it. This article focuses on a case study that examines multilingual communication strategies and practices coordinated during the pandemic by the Direction régionale de santé publique de Montréal. Drawing on documentary evidence and semi-structured interviews, the article reveals that Santé publique Montréal integrated a multilingual approach into its emergency communication strategy after the first wave of the pandemic, which resulted in more translations of COVID-19 information, and the implementation of bottom-up communication practices in collaboration with community-based organisations to build trust. The article also shows that the pandemic paved the way for a risk-based approach to language management capable of helping us rethink multilingualism management in Canada and beyond.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it