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Record W4324136364 · doi:10.1111/jtsb.12379

Constructing the Anti‐Vaxxer: Discursive analysis of public deliberations on childhood vaccination

2023· article· en· W4324136364 on OpenAlexafffund
Jessica B. C. White, Kieran C. O’Doherty

Bibliographic record

VenueJournal for the Theory of Social Behaviour · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of Guelph
FundersOntario Ministry of Research and InnovationCanadian Institutes of Health Research
KeywordsDeliberationNormativeArgument (complex analysis)EpistemologySociologyFocus (optics)Focus groupPublic discoursePsychologySocial psychologyPublic relationsPolitical scienceLawPoliticsMedicine

Abstract

fetched live from OpenAlex

Abstract Public deliberation is a form of dialogue that allows members of the public to provide input on a policy issue. Public deliberation processes invite participants to engage with each other respectfully, learn about the topic and each other's perspectives, and then work together toward solutions to an issue that are broadly acceptable. In this article, we develop a discursive psychological analysis of public deliberation on the topic of childhood vaccination. In particular, we focus on how descriptions of a parent who did not have her children vaccinated were developed iteratively by a small group of deliberants; how these descriptions came to be accepted as factual; and how these descriptions came to be used to support normative claims about childhood vaccination. Our main argument is that we can develop a deeper understanding of deliberation processes if we understand participants' statements to be rhetorically organised. This is achieved by examining how descriptions of events or people that are relevant to the final conclusions of the group are developed in the course of deliberation; how they come to be accepted as factual and accurate by the group; and how they then become instrumental in supporting a final consensus position.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.056
GPT teacher head0.370
Teacher spread0.314 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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
Published2023
Admission routes2
Has abstractyes

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