Questioning Competence: A Discourse Analysis of Attending Physicians’ Use of Questions to Assess Trainee Competence
Bibliographic record
Abstract
BACKGROUND: Attending physicians (APs) must constantly assess trainees' competence to act independently, to promote learning while ensuring quality of care. This study aimed to explore, through discourse analysis of case presentations, the process of competence assessment for case-specific clinical independence. METHOD: Twenty-six case presentations in emergency medicine were observed and audiorecorded. A discourse analysis was conducted, focusing on APs' use of questioning strategies. RESULTS: Questioning strategies involved clarifying questions (to ensure APs' understanding of the case), probing questions (to probe trainees' understanding of a case or their underlying knowledge), and challenging questions (to challenge presuppositions). Case-related probing questions and challenging questions were found to be linguistic features of APs' assessments of trainees' competence. CONCLUSIONS: The identification of specific linguistic features of the process of competence assessment by APs provides a framework for faculty development and future study of the function and effects of such discourse patterns.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".