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Record W3137770325 · doi:10.1093/jtm/taab048

What must be done to tackle vaccine hesitancy and barriers to COVID-19 vaccination in migrants?

2021· article· en· W3137770325 on OpenAlexaff
Alison F Crawshaw, Anna Deal, Kieran Rustage, Alice S. Forster, Inês Campos-Matos, Tushna Vandrevala, Andrea Würz, Anastasia Pharris, Jonathan E. Suk, John Kinsman, Charlotte Deogan, Anna N. Miller, Silvia Declich, Chris Greenaway, Teymur Noori, Sally Hargreaves

Bibliographic record

VenueJournal of Travel Medicine · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsMcGill University
FundersMedical Research CouncilMechanics Electronics Computer CorporationDepartment of Health and Social CareRosetrees TrustNational Institute on Handicapped ResearchAcademy of Medical SciencesEuropean Society of Clinical Microbiology and Infectious DiseasesNational Institute for Health and Care Research
KeywordsMedicineCoronavirus disease 2019 (COVID-19)Vaccination2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Herd immunityEnvironmental healthVirologyFamily medicineOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Migrants have been disproportionately impacted by COVID-19 and emerging evidence suggests they may face barriers to COVID-19 vaccination. Participatory approaches and engagement strategies are urgently needed to strengthen uptake, alongside innovative delivery mechanisms and sharing of best practice, to ensure migrants are better consider within countries’ existing vaccine priority structures.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.036
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0080.014
Open science0.0030.007
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0160.002

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 head0.032
GPT teacher head0.347
Teacher spread0.315 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations161
Published2021
Admission routes1
Has abstractyes

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