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Record W4293053482 · doi:10.47989/irpaper931

‘In a perfect world doctors and the medical profession would accept people for who they are’: women’s heart health information practices

2022· article· en· W4293053482 on OpenAlexaboutno aff
Tami Oliphant, Tany Berry, Colleen M. Norris

Bibliographic record

VenueInformation Research an international electronic journal · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisExperiential knowledgePersonal information managementFatalismMedicinePsychologySocial psychologyQualitative researchSociologyInformation systemManagement information systemsSocial sciencePolitical science

Abstract

fetched live from OpenAlex

Introduction. This exploratory study investigates women’s health information practices by examining how women perceive and interpret heart health information from organizations such as Heart & Stroke Canada that are targeted specifically to them. Method. Focus groups were conducted with women (45 – 90 years) with heart disease and without heart disease and three women with heart disease participated in semi-structured interviews. Analysis. The data were analysed using thematic analysis. Five themes that shaped women’s perceptions and interpretations of heart health information were identified: personal expertise and experiential knowledge, consistency in information content, embodied information, ability to act on information, and shame and blame. Results. Women draw from epistemic, social, and corporeal information sources in order to make sense of heart disease. Coupling corporeal and experiential knowledge are important for women to triangulate information. Women’s heart health information practices occur within an androcentric, sociocultural context where broader social information sources that focus on ‘ideal’ health standards must align with women’s lived experiences in order for the information to be acted upon. Conclusions.To craft more effective messages and provide helpful information about heart health, messages and information must align with women’s information practices in ways that acknowledge the intersections and consistency of epistemic, social, and corporeal information sources and the information must be actionable.

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)0.061
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0610.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.000
Scholarly communication0.0000.018
Open science0.0010.000
Research integrity0.0000.008
Insufficient payload (model declined to judge)0.0040.000

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 head0.060
GPT teacher head0.534
Teacher spread0.474 · 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 designNot applicable
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

Citations5
Published2022
Admission routes1
Has abstractyes

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