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Record W4306175226 · doi:10.1177/10693971221134181

Communism’s Lasting Effect? Former Communist States and COVID-19 Vaccinations

2022· article· en· W4306175226 on OpenAlexaff
Jason P. Martens

Bibliographic record

VenueCross-Cultural Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCulture, Economy, and Development Studies
Canadian institutionsCapilano University
Fundersnot available
KeywordsCommunismDistrustGovernment (linguistics)Political scienceDevelopment economicsPopulationDemographyEconomic historyPolitical economyDemographic economicsGeographySociologyHistoryPoliticsEconomicsLaw

Abstract

fetched live from OpenAlex

Historical cultural practices that no longer exist can have modern day effects. Because communism has been linked with distrust of government, it was hypothesized that (a) historical communism would be negatively associated with COVID-19 vaccination rates, and (b) trust in government would mediate the association. Two studies assessed these hypotheses. Study 1 tested the hypotheses among European, Asian, and African countries, while Study 2 focused on East and West Germany within Europe. All samples except Africa found support for an association between historical communism and lower COVID-19 vaccination rates. However, trust in government did not mediate the association in Study 1, though a significant indirect effect did emerge within Germany in Study 2. Associations held controlling for GDP and age of population. Together, the studies suggest that historical communism in Europe and Asia is associated with real-world behavior today, and that trust in government might be partly responsible for the effect within Germany but less likely within Europe as a whole.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0260.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.178
GPT teacher head0.521
Teacher spread0.343 · 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 designNot applicable
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

Citations4
Published2022
Admission routes1
Has abstractyes

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