Covid-19 vaccine hesitancy policy tools in western Canada
Bibliographic record
Abstract
Canada’s four western provinces largely converged in implementing Covid-19 vaccine hesitancy and uptake policy tools. This thesis analyzes these tools and focuses on vaccine mandates, vaccine passports, and related policy tools. The method applied was data analysis, and two frameworks, a policy tool framework and a vaccine hesitancy framework, were applied. Using these, information was interpreted from two sources of grey literature, government websites and news media articles published from late 2020 to early 2022. All four western provincial governments were found to substantially adopt agreed upon recommendations from scholars in the fields of public health, public health communication, and vaccination. Manitoba was most successful in adopting these measures, followed by Saskatchewan, but counter to expert recommendations, Alberta implemented extensive financial inducements to improve vaccination uptake. While BC obtained the highest vaccination rates, it was the only province of the four that did not provide an option of testing in lieu of vaccination, a decision by the Minister of Health. This was the case for employees in its public service agency, its healthcare sector, or for residents in general regarding its vaccine passport. Vaccine passports and vaccine mandates raised concerns about informed consent. This exhibited a clash between principles of governance involving the legitimate use of coercion, and how informed consent in medicine requires the absence of coercion. This thesis argues that, in some cases, these actions violated the Charter protected right to bodily integrity. These concerns implied one of two requirements regarding vaccine passports and vaccine mandates: either a clear expression of specific risks proportional to their coercive force as justification, which was not forthcoming; or mitigation of their coercive force, which testing in lieu accomplished. Therefore, three of the western provinces substantially met the ethical requirements implied by their vaccine passports and vaccine mandates by implementing the mitigating option of testing in lieu. Yet based on the criteria as established in this thesis, BC did not meet these ethical requirements.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".