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Record W2888394224 · doi:10.1016/j.vaccine.2018.08.042

Mandatory infant & childhood immunization: Rationales, issues and knowledge gaps

2018· review· en· W2888394224 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.

Bibliographic record

VenueVaccine · 2018
Typereview
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsPublic Health OntarioIzaak Walton Killam Health CentreInstitut National de Santé Publique du QuébecUniversité LavalUniversity of TorontoDalhousie University
FundersWorld Health Organization
KeywordsImmunizationContext (archaeology)PopulationPsychological interventionMedicineIncentiveEnforcementEnvironmental healthBusinessPediatricsEconomic growthEconomicsPolitical scienceImmunologyNursingGeography

Abstract

fetched live from OpenAlex

Globally, infant and childhood vaccine uptake rates are not high enough to control vaccine preventable diseases, with outbreaks occurring even in high-income countries. This has led a number of high-, middle-and low income countries to enact, strengthen or contemplate mandatory infant and/or childhood immunization to try to address the gap. Mandatory immunization that reduces or eliminates individual choice is often controversial. There is no standard approach to mandatory immunization. What vaccines are included, age groups covered, program flexibility and rigidity e.g. opportunities for opting out, penalties or incentives, degree of enforcement, and whether a compensation program for causally associated serious adverse events following immunization exists vary widely. We present an overview of mandatory immunization with examples in two high- and one low-income countries to illustrate variations, summarize limited outcome data related to mandatory immunization, and suggest key elements to consider when contemplating mandatory infant and/or child immunization. Before moving forward with mandatory immunization, governments need to assure financial sustainability, uninterrupted supply and equitable access to all the population. Other interventions may be more effective and less intrusive than mandatory. If mandatory is implemented, this needs to be tailored to fit the context and the country's culture.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.755
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.037
GPT teacher head0.359
Teacher spread0.322 · 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