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Record W2021763032 · doi:10.1016/j.vaccine.2015.04.042

Health communication and vaccine hesitancy

2015· article· en· W2021763032 on OpenAlexaff
Susan Goldstein, Noni E. MacDonald, Sherine Guirguis

Bibliographic record

VenueVaccine · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsHealth communicationSelection (genetic algorithm)Key (lock)Process (computing)Risk communicationImmunizationPlan (archaeology)Public relationsComputer sciencePsychologyKnowledge managementProcess managementMedicineRisk analysis (engineering)BusinessBiologyPolitical scienceImmunologyComputer securityArtificial intelligence

Abstract

fetched live from OpenAlex

Health communication is an evolving field. There is evidence that communication can be an effective tool, if utilized in a carefully planned and integrated strategy, to influence the behaviours of populations on a number of health issues, including vaccine hesitancy. Experience has shown that key points to take into account in devising and implementing a communication plan include: (i) it is necessary to be proactive; (ii) communication is a two-way process; (iii) knowledge is important but not enough to change behaviour; and (iv) communication tools are available and can be selected and used creatively to promote vaccine uptake. A communication strategy, incorporating an appropriate selection of the available communication tools, should be an integral part of every immunization programme, addressing the specific factors that influence hesitancy in the target populations.

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)0.004
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.038
GPT teacher head0.329
Teacher spread0.291 · 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 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

Citations276
Published2015
Admission routes1
Has abstractyes

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