From behaviours to attributions: further concerns regarding the evaluation of professionalism
Bibliographic record
Abstract
OBJECTIVES: This study aimed to explore faculty attendings' scoring and opinions of students' written responses to professionally challenging situations. METHODS: In this mixed-methods study, 10 pairs of faculty attendings (attending physicians in internal medicine) marked responses to a professionalism written examination taken by 40 medical students and were then interviewed regarding their scoring decisions. Quantitatively, inter-rater scoring agreement was calculated for each pair and students' global scores were compared with a previously developed theoretical framework. Qualitatively, interviews were analysed using grounded theory. RESULTS: Inter-rater reliability in scoring was poor. There was also no correlation between faculty's scores and our previous theoretical framework; this lack of correlation persisted despite modifications to the framework. Qualitative analysis of faculty attendings' interviews yielded three major themes: faculty preferred responses in which students expressed insight, showed responsibility, and ultimately put the patient first. Faculty also expressed difficulty in deciding what was more important (the behaviour or the rationale behind it) and in assigning numerical scores to students' responses. Interestingly, they did not downgrade students for mentioning implications for themselves as long as these were balanced by other considerations. CONCLUSIONS: This study attempted to overcome some of the instability that results when we judge behaviours by making the rationales behind students' behaviours explicit. However, between-faculty agreement was still poor. This reinforces concerns that professionalism, as a subtle and complex construct, does not reduce easily to numerical scales. Instead of concentrating on creating the 'perfect' evaluation instrument, educators should perhaps begin to explore alternative approaches, including those that do not rely on numerical scales.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".