Personal Responsibility for Health: Exploring Together with Lay Persons
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.029 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".