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Record W2605291914 · doi:10.1093/pch/18.5.268

Les parents qui hésitent à faire vacciner leur enfant : une approche clinique

2013· article· fr· W2605291914 on OpenAlexaboutno aff
Noni E. MacDonald, Jane C Finlay

Bibliographic record

VenuePaediatrics & Child Health · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La plupart des parents canadiens s’assurent de faire vacciner leur enfant aux moments prévus, mais quelques-uns sont hésitants à l’égard de la vaccination, la reportent ou refusent carrément les vaccins recommandés. Le présent point de pratique offre aux cliniciens des conseils probants sur la manière d’aborder les parents qui hésitent à faire vacciner leur enfant, notamment ceux qui s’inquiètent de l’innocuité vaccinale. Les étapes proposées consistent à comprendre les inquiétudes précises des parents à l’égard des vaccins, à utiliser les techniques d’entrevue motivationnelle, à s’en tenir au message et à utiliser un langage clair pour présenter les données probantes sur les risques des maladies ainsi que sur les bienfaits et les risques des vaccins de manière juste et précise, à informer les parents de la rigueur du système d’innocuité vaccinale, à aborder la question de la douleur causée par la vaccination et à éviter de bannir des enfants d’un cabinet parce que les parents refusent de le faire vacciner. Puisque la vaccination est l’une des mesures de santé préventive les plus importantes, grâce à laquelle on sauve littéralement des millions de vies, les dispensateurs de soins doivent se donner comme priorité de calmer les inquiétudes des parents qui hésitent à faire vacciner leur enfant.

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)0.060
metaresearch head score (Gemma)0.129
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.319

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.129
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0030.003
Scholarly communication0.0080.006
Open science0.0030.005
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0110.004

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 head0.029
GPT teacher head0.315
Teacher spread0.287 · 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 designQualitative
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

Citations1
Published2013
Admission routes1
Has abstractyes

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