Public attitudes towards COVID-19 vaccine mandates and vaccine certificates in Canada: a time series study
Bibliographic record
Abstract
Abstract Introduction Since the beginning of the pandemic, numerous public health measures such as COVID-19 vaccines, vaccine mandates and vaccination certificates have been introduced to mitigate the spread of COVID-19. Public opinion and attitudes towards these measures have fluctuated in response to the dynamic political, social, and cultural landscape of the pandemic. Methods We conducted a time-series study consisting of national cross-sectional surveys between November 2021 to March 2022 to evaluate the Canadian public’s attitudes towards COVID-19 vaccine mandates and vaccine certificates. Results When examining public sentiment towards COVID-19 vaccine certificates and proof of vaccination measures, there was a shift in responses over time. The proportion of participants “strongly supporting” these measures decreased from 66.0–43.1% between W25(Capacity Limits), –W32 (Mask Mandate Removed), whereas “strongly oppose” was the second most common response and rose from 15.9–20.6% during this same time period. Concurrently, when examining participants views surrounding mandates, many participants believed that their province was reopening at “about the right pace”, which remained relatively stable over time (33.0–35.4%) between W28 (Emergency Act)–W32 (Mask Mandate Removed). Conclusion Our study’s findings on the public’s attitudes towards COVID-19 vaccine mandates and vaccine certificates in Canada may aid to guide and streamline the implementation of future similar public health interventions. Future research should include extended follow-up and a more comprehensive examination of trust in government institutions and polarized perspectives on vaccine mandates.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".