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Record W4386547660 · doi:10.12927/hcpol.2023.27153

COVID-19 Vaccine’s Speed to Market and Vaccine Hesitancy: A Cross-Sectional Survey Study

2023· article· en· W4386547660 on OpenAlexafffundvenueabout
Ally Memedovich, Brenlea Farkas, Aidan Hollis, Charleen Salmon, Jia Hu, Kate Zinszer, Tyler Williamson, Reed F. Beall

Bibliographic record

VenueHealthcare policy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsAlberta Health ServicesUniversité de MontréalAlberta HealthUniversity of Calgary
FundersCanadian Institutes of Health ResearchUniversity of Calgary
KeywordsCoronavirus disease 2019 (COVID-19)TimelineCross-sectional studyPandemicMedicine2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Family medicineVaccinationEnvironmental healthVirologyGeographyOutbreakInternal medicine

Abstract

fetched live from OpenAlex

Background: This paper aims to assess the extent to which the COVID-19 vaccine's speed to market affected Canadian residents' decision to remain unvaccinated. Method: A cross-sectional survey conducted in late 2021 asked participants whether they had received the vaccine and their reasons for abstaining. Results: Of the 2,712 participants who completed the survey, 8.9% remained unvaccinated. Unvaccinated respondents who selected "They made the vaccine too fast" (59.8%), were significantly more likely to identify as white, believe that the COVID-19 pandemic was not serious and have an unvaccinated social circle. Conclusion: Should the COVID-19 vaccine rapid regulatory process be expanded, more patients may refuse treatment than if traditional timelines are followed.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.102
GPT teacher head0.453
Teacher spread0.351 · 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

Citations3
Published2023
Admission routes4
Has abstractyes

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