Guidelines for the administration of oral examinations
Bibliographic record
Abstract
Practical oral examinations are considered an important and often a difficult part of medical school examinations. They represent an accurate and direct mean of assessing student's interaction with patients and their clinical and technical skills. This paper reviews an outline for the administration of oral examinations. The review is based on the medical literature detailed discussions with many senior examiners from different medical systems, and the author's personal experience. In summary, although examiner's judgment is crucial, some general rules remain important for fair and consistent evaluation of students. First, examiner's attitudes should be as friendly as possible with an objective aimed to assess student's medical competence and practical safety. Secondly, scoring should be based on a model answer or well-accepted medical practices for consistent rating. Finally, each examiner should give an independent score before discussing the final rating with the other examiners.
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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 | 0.028 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.019 | 0.032 |
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".