From concern for patients to a quest for information
Bibliographic record
Abstract
This study of social representations about interpreted medical consultations examines the discourse of French language focus groups (FGs), conducted in Quebec, with 22 third year medical students (4 FGs), 29 family medicine residents (4 FGs) and 47 experienced family physicians (5 FGs). The audio-recorded FGs were transcribed. Each discussed two video vignettes of interpreted consultations. Statistical textual analysis showed that the students’ discourse patterns differed by FG. Residents prioritized access to the patient’s culture via the interpreter, though recognizing the need to respect the patient-physician relationship. Senior physicians organized their discourse differently for each vignette, associating it with a ‘standard’ response: for them, the two main issues were the quest for information, which we relate to the medical socialization process; and the interpreter’s stances, in terms of how s/he is perceived by physicians and the role(s) s/he is seen to play in the consultation. Physicians tend to represent the interpreter as a controllable ‘object’, not a full-fledged healthcare professional.
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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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".