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Record W3185426568 · doi:10.1139/facets-2021-0037

Royal society of Canada COVID-19 report: Enhancing COVID-19 vaccine acceptance in Canada

2021· article· en· W3185426568 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFACETS · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsHospital for Sick ChildrenYork UniversityUniversity of GuelphNOSM UniversityHealth Sciences NorthMcMaster Children's HospitalUniversity of Northern British ColumbiaUniversité LavalInstitut National de Santé Publique du QuébecIzaak Walton Killam Health CentreUniversity of TorontoDalhousie University
FundersUniversity of AlbertaYork UniversityMcMaster UniversityUniversity of TorontoDalhousie UniversityUniversity of Ottawa
KeywordsVaccinationIndigenousCoronavirus disease 2019 (COVID-19)Health carePublic healthImmunizationBusinessPublic relationsEconomic growthPolitical scienceMedicineNursingInfectious disease (medical specialty)Immunology

Abstract

fetched live from OpenAlex

COVID-19 vaccine acceptance exists on a continuum from a minority who strongly oppose vaccination, to the “moveable middle” heterogeneous group with varying uncertainty levels about acceptance or hesitancy, to the majority who state willingness to be vaccinated. Intention for vaccine acceptance varies over time. COVID-19 vaccination decisions are influenced by many factors including knowledge, attitudes, and beliefs; social networks; communication environment; COVID-19 community rate; cultural and religious influences; ease of access; and the organization of health and community services and policies. Reflecting vaccine acceptance complexity, the Royal Society of Canada Working Group on COVID-19 Vaccine Acceptance developed a framework with four major factor domains that influence vaccine acceptance (people, communities, health care workers; immunization knowledge; health care and public health systems including federal/provincial/territorial/indigenous factors)—each influencing the others and all influenced by education, infection control, extent of collaborations, and communications about COVID-19 immunization. The Working Group then developed 37 interrelated recommendations to support COVID vaccine acceptance nested under four categories of responsibility: 1. People and Communities, 2. Health Care Workers, 3. Health Care System and Local Public Health Units, and 4. Federal/Provincial/Territorial/Indigenous. To optimize outcomes, all must be engaged to ensure co-development and broad ownership.

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.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.299
Teacher spread0.278 · 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