COVID-19 Vaccine Mandates and a Freedom Convoy: A Transdisciplinary Framework for Analyzing Meaning in Health Risk Communication
Bibliographic record
Abstract
Scholars in health risk communication offer evidence-based guidance for effectively communicating risk to the public. However, existing research rarely examines the discursive realizations of these communicative strategies, which is where meaning is made in language. This transdisciplinary study introduces a framework for analyzing health risk communication, assessing the discourse using standards of risk communication and methods of systemic functional linguistics and critical discourse studies. The study applies the framework to a news release and a backgrounder released by the Ontario government to communicate new public health measures responding to the first Omicron variant of COVID-19. The findings indicate that neither text empowers the public to take informed decisions to mitigate health risks, which is the purpose of risk communication. The texts fail to implement the standards of the CORA framework for communicating risk in a context of scientific uncertainty and display patterns of verb transitivity that could polarize public response. I'm deeply grateful to my supervisors, Dr. Rachelle Vessey and Dr. Jaffer Sheyholislami, for their guidance,
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".