Comparing Ideology and COVID-19 Preferences of Canadian Public Health Workers and the General Population
Bibliographic record
Abstract
Objectives: This study tests whether and how the Canadian public health workforce differed from the Canadian general population in their political attitudes, worldviews and policy preferences related to the COVID-19 pandemic. Methods: Nearly identical surveys were fielded to the Canadian public health workforce in 2021 through leading public health associations and to a census-balanced sample of the general Canadian population in February and March 2021. through a consumer quota sample for a survey of the general population. Results: The Canadian public health workforce demonstrates systematically more left-wing pro-egalitarian, anti-hierarchical, anti-individualist worldviews. Those in health promotion positions are slightly more to the left than those in non-health promotion positions. However, the public health sample did not uniformly favour stricter COVID-19 containment and prevention policies than the general population. When modelling COVID-19 prevention policies as a function of cultural worldviews and ideology, it appeared that these had a greater effect on policy preferences in the general population than in the public health sample. Conclusion: The public health workforce is more left-wing than the general population and professionals in health promotion positions are more left-wing than others in public health. But the public health workforce did not uniformly prefer stricter COVID-19 prevention policies. Cultural worldviews and ideology were stronger predictors of policy preferences for the general population than for the public health sample respondents.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".