Exploring the Public Health Agency of Canada's and the Ontario government's vaccine-related crisis communication on X during the COVID-19 pandemic
Bibliographic record
Abstract
Crisis communication strategies must be tailored to the unique nature of social media. In response to the COVID-19 pandemic, public health agencies have widely used social media to address vaccine hesitancy and misinformation. This research utilized the social media pandemic communication model to describe the key themes disseminated through the Ontario government and the Public Health Agency of Canada's vaccine-related crisis communication on X (formerly Twitter). Between 27 January 2020 and 6 April 2021, 1271 posts related to COVID-19 vaccination were collected from three official government X accounts—two from the province of Ontario and one from Canada. Posts were analyzed and coded according to their message characteristics, main themes, and sub-themes. Both levels of government expressed similar themes of vaccine safety, benefits of vaccination, and addressed vaccine hesitancy; however, differed in terms of their messaging strategies used.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".