Types of clinical reasoning in a summative clerkship oral examination
Bibliographic record
Abstract
Dual-process theory characterizes clinical reasoning (CR) as Type 1 (intuitive) and Type 2 (analytical) thinking. This study examined CR on a summative clinical clerkship structured clinical oral examination (SCOE). 511 clinical clerks at the University of Toronto underwent SCOEs. Type 1, Type 2, and Global CR performance were compared to other internal medicine clerkship assessments using descriptive statistics and Spearman correlations. Clinical clerks achieved mean marks >75% on the three clinical reasoning stations, on Type 1 and 2 CR tasks, and the overall SCOE. Performance on the SCOE CR stations correlated with each of the other clerkship assessments: written examination, inpatient, and ambulatory clinic assessments. The correlation of performance between Type 1 and Type 2 clinical reasoning tasks was statistically significant but weak (rs = 0.28). This suggests that defined measures of Type 1 and Type 2 reasoning were indeed assessing distinct constructs. Clinical clerks used both Type 1 and Type 2 reasoning with success. This study’s characterization of Type 1 and Type 2 CR as separate domains, distinct from existing measures on the SCOE as well as the other clerkship assessments, can suggest a further addition to multimodal clerkship assessment.
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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 | 0.014 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".