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Record W2017939023 · doi:10.4161/21645515.2014.970076

When knowledge is not enough: Changing behavior to change vaccination results

2014· letter· en· W2017939023 on OpenAlexaff
Kimberly Corace, Gary Garber

Bibliographic record

VenueHuman Vaccines & Immunotherapeutics · 2014
Typeletter
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsPublic Health OntarioUniversity of TorontoOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsVaccinationPsychological interventionHealth careMedicineHealth promotionPromotion (chess)Behavior changeEnvironmental healthFamily medicineNursingPublic healthImmunologyPolitical science

Abstract

fetched live from OpenAlex

Why don't health care workers universally embrace vaccination to prevent vaccine preventable diseases and protect themselves and their patients? To address this problem most vaccination campaigns focus on providing education and information to health care workers. While knowledge is a necessary first step, it is likely not sufficient to increase health care worker vaccine uptake. We discuss a novel approach to applying behavior change theories and principles as a framework to plan, guide, and evaluate vaccine promotion interventions, with the goal of enhancing vaccine coverage among health care workers.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.124
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.113
GPT teacher head0.363
Teacher spread0.250 · 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; both teacher heads agree on what is shown here.

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

Citations77
Published2014
Admission routes1
Has abstractyes

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