Conservative Ideologies in Canada and the United States Predict Poorer Pandemic Outcomes
Bibliographic record
Abstract
Purpose: We conducted studies in two Western, individualistic countries, Canada and the United States, to assess the impact of political ideology on governmental policies (e.g., implementation of mask mandates) and individual conduct (e.g., getting vaccinated) in response to the COVID19 pandemic, as well as infection and death rates. We argue that conservative political ideology is associated with poorer handling of COVID-19. Methods (Study 1): The relationship between whether or not a conservative majority held power in Canadian provinces and territories and COVID-19 infection and death rates in nursing homes and the general population, business insolvencies, implementation of mask mandates or travel bans, allowed religious gathering sizes, anti-mask and anti-lockdown protests, and vaccination rates was examined. Results (Study 1): Infection and death rates in conservative provinces were higher and rose faster. Conservative provinces had higher infection and death rates in nursing homes, had more business insolvencies, took longer to introduce mask mandates and dropped them sooner, allowed larger religious gatherings, and took longer to introduce interprovincial travel bans (or had none). Residents of conservative provinces were more likely to engage in anti-mask and anti-lockdown protests, and less likely to have been vaccinated. Methods (Study 2): Study 2 examined similar variables in the United States as a function of the percentage of states’ votes for Donald Trump (the more conservative candidate) in the 2020 U.S. Presidential election. Results (Study 2): Infection and death rates were higher in conservative states (those with a higher percentage of Trump voters) than more liberal states (those with a lower percentage of Trump voters). Conservative states also were less likely to mandate masks or did so later, were less likely to close businesses or issue stay at home orders, reopened schools for in-person learning sooner, and had lower vaccination rates; all of these differences were related to infection and death rates. Conclusion: Our data suggest that conservative governments have had poorer responses to the pandemic than more liberal governments, and conservative individuals have lower vaccination rates than their more liberal counterparts, resulting in higher infection and death rates. Public health measures such as vaccinations and masking are essential for controlling infectious diseases, but their success depends fundamentally on the social behavior of governments and individuals.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".