Socially constructed and structurally conditioned conflicts in territories of medical uncertainty
Bibliographic record
Abstract
In territories of medical uncertainty, clinical encounters are highly contentious. To uncover maintaining mechanisms behind persistent conflicts, we explore the interactional dynamics of clinical encounters fused with medical uncertainty. Based on a thematic qualitative analysis of experiential texts from 385 people living with medically unexplained physical symptoms in Norway, UK, Ireland, USA and Canada, we explore patients’ main expectations, how these expectations are met, and how their expectations and experiences are socially constructed and structurally conditioned. Five fundamental expectations are identified: Health professionals ought to (1) acknowledge the lack of medical knowledge, and be frank, open and curious about it; (2) believe patient experiences and accept their condition as “real”; (3) avoid blaming patients for their ailment; (4) demonstrate compassion, understanding and respect; and (5) share decision-making power with patients. Our participants experience unfulfilled expectations in all five areas. Both experiences and unfulfilled expectations are influenced by structural factors transpiring from the modern Western biomedical paradigm, and from cultural norms and values of its surrounding society. Structural and cultural forces obstruct team-oriented collaboration based on congruent understandings, mutual trust and reciprocated respect. Without such contextualisation, the interactional dynamics between patients and health professionals in clinical consultations cannot be exposed.
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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 | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.048 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".