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Record W4362480352 · doi:10.18103/mra.v11i3.3585

Conservative Ideologies in Canada and the United States Predict Poorer Pandemic Outcomes

2023· article· en· W4362480352 on OpenAlexaboutno aff
Robert Sinclair, Jeffrey S. Melton

Bibliographic record

VenueMedical Research Archives · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyDemographyPandemicMortality ratePopulationPoliticsCoronavirus disease 2019 (COVID-19)Presidential systemMedicinePolitical scienceDemographic economicsPolitical economyLawSociologyEconomicsDisease

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.034
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.119
GPT teacher head0.352
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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