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Record W4415254313 · doi:10.47854/pnsc1j78

Vaccination

2025· article· W4415254313 on OpenAlexaffvenue
Ève Dubé, Benjamin Malo

Bibliographic record

VenueAnthropen · 2025
Typearticle
Language
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsVaccinationFace (sociological concept)Psychological interventionIdentity (music)

Abstract

fetched live from OpenAlex

La vaccination est l’une des interventions les plus efficaces en santé publique après l’accès à l’eau potable. Bien plus qu’une technologie biomédicale, elle est profondément ancrée dans des contextes historiques, sociaux et politiques. Si l’histoire de la vaccination remonte à la variolisation en Asie et en Afrique, l’anthropologie s’y est intéressée plus récemment, notamment avec le Programme élargi de vaccination de l’OMS. Les anthropologues analysent les résistances vaccinales non comme un simple refus irrationnel, mais comme des réactions enracinées dans des expériences de marginalisation, des mémoires coloniales ou des tensions sociopolitiques. Ils examinent aussi l’influence des rumeurs, des espaces numériques, des relations soignants-soignés et des inégalités d’accès. Cette approche critique et contextuelle relie le micro social au macro social.

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)0.002
metaresearch head score (Gemma)0.005
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.242
Threshold uncertainty score0.808

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2420.108

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 head0.020
GPT teacher head0.356
Teacher spread0.336 · 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
GenreOther

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

Citations0
Published2025
Admission routes2
Has abstractyes

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