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Record W4287377085 · doi:10.1093/phe/phac009

Personal Responsibility for Health: Exploring Together with Lay Persons

2022· article· en· W4287377085 on OpenAlex
Yukiko Asada, Marion Brown, Mary McNally, Andrea Murphy, Robin Urquhart, Grace Warner

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePublic Health Ethics · 2022
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchNova Scotia Department of Health and WellnessNova Scotia Health Research Foundation
KeywordsMoral responsibilityThematic analysisSocial psychologyPsychologyHealth careSocial responsibilityEquity (law)SociologyPublic relationsQualitative researchPolitical scienceLawSocial science

Abstract

fetched live from OpenAlex

Abstract Emerging parallel to long-standing, academic and policy inquiries on personal responsibility for health is the empirical assessment of lay persons’ views. Yet, previous studies rarely explored personal responsibility for health among lay persons as dynamic societal values. We sought to explore lay persons’ views on personal responsibility for health using the Fairness Dialogues, a method for lay persons to deliberate equity issues in health and health care through a small group dialogue using a hypothetical scenario. We conducted two 2-h Fairness Dialogues sessions (n = 15 in total) in Nova Scotia, Canada. We analyzed data using thematic analysis. Our analysis showed that personal choice played an important role in participants’ thinking about health. Underlying the concept of personal choice was considerations of freedom and societal debt. In participants’ minds, personal and social responsibilities co-existed and they were unwilling to determine health care priority based on personal responsibility. The Fairness Dialogues is a promising deliberative method to explore lay persons’ views as dynamic values to be developed through group dialogues as opposed to static, already-formed values waiting to be elicited.

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.

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)0.129
metaresearch head score (Gemma)0.056
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.848
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1290.056
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0170.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.027
Insufficient payload (model declined to judge)0.0020.000

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 head0.603
GPT teacher head0.573
Teacher spread0.031 · 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