MétaCan
Menu
Back to cohort
Record W2803625688 · doi:10.3390/ijerph15051044

The Social Basis of Vaccine Questioning and Refusal: A Qualitative Study Employing Bourdieu’s Concepts of ‘Capitals’ and ‘Habitus’

2018· article· en· W2803625688 on OpenAlexaff
Katie Attwell, Samantha B. Meyer, Paul Ward

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsUniversity of Waterloo
FundersFlinders FoundationSanofi PasteurDepartment of Health, Government of Western AustraliaFlinders Medical Centre FoundationSanofi
KeywordsHabitusStatus quoConformitySociologyQualitative researchSocial psychologyCompliance (psychology)Social capitalPublic relationsPsychologyCultural capitalSocial sciencePolitical science

Abstract

fetched live from OpenAlex

This article is an in-depth analysis of the social nature of vaccine decision-making. It employs the sociological theory of Bourdieu and Ingram to consider how parents experience non-vaccination as a valued form of capital in specific communities, and how this can affect their decision-making. Drawing on research conducted in two Australian cities, our qualitative analysis of new interview data shows that parents experience disjuncture and tugs towards 'appropriate' forms of vaccination behavior in their social networks, as these link to broader behaviors around food, school choices and birth practices. We show how differences emerge between the two cities based on study designs, such that we are able to see some parents at the center of groups valorizing their decisions, whilst others feel marginalized within their communities for their decisions to vaccinate. We draw on the work of philosopher Mark Navin to consider how all parents join epistemic communities that reward compliance and conformity with the status quo and consider what this means for interventions that seek to influence the flow of pro-vaccine information through vaccine-critical social groups.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.103
GPT teacher head0.517
Teacher spread0.415 · 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.

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

Citations80
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Environmental Research and Public HealthSame topicVaccine Coverage and HesitancyFrench-language works237,207