Medical teachers’ discursive positioning of doctors in relation to patients
Bibliographic record
Abstract
CONTEXT: An important part of a doctor's identity is the social position he or she adopts relative to patients. Dialogic theory predicts that medical school discourses influence the positions students incorporate into their professional identities. As this may affect how students later exercise power in doctor-patient relationships, we set out to examine how medical teachers position doctors in relation to patients. METHODS: Informed by Holland's Figured Worlds theory, which draws important assumptions from Bakhtin, we chose dialogic research methodology to examine how educators' language positions doctors and may influence students' identity formation. We recruited a maximum variation sample of 10 teaching staff and used open prompts in individual semi-structured interviews to elicit discourses of doctors' social position. We used Sullivan's dialogic methodology reflexively to identify informative speech acts (utterances) and to examine how the language used in these constructed doctors' positions. RESULTS: Dominant discourses of Social Superiority, Technical Effectiveness, and Benevolence elevated doctors' positions based on their social status, applied knowledge and trustworthiness, respectively. These positions were defended by predicating medical care on doctors' mastery of treatments and their superior knowledge. A non-dominant discourse of Distributed Power and Responsibility narrowed the positional gap by constructing doctors as empowering patients. CONCLUSIONS: Whereas three conservative discourses upheld doctors' elevated social position, a non-dominant, transformative discourse distributed power. We suggest that doctors will form the best relationships with patients when they are aware of these discourses and know how to navigate them. In pursuit of effective and compassionate patient care, we commend critical pedagogy as a means of articulating non-dominant discourses and increasing students', educators' and doctors' awareness of how they learn the positions of doctors.
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 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 | 0.011 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".