Observation, Reflection, and Reinforcement: Surgery Faculty Membersʼ and Residentsʼ Perceptions of How They Learned Professionalism
Bibliographic record
Abstract
PURPOSE: To explore perceptions of how professionalism is learned in the current academic environment. Professionalism is a core competency in surgery (as in all of medical practice), and its presence or absence affects all aspects of clinical education and practice, but the ways in which professional values and attitudes are best transmitted to developing generations of surgeons have not been well defined. METHOD: The authors conducted 34 semistructured interviews of individual surgery residents and faculty members at two academic institutions from 2004 to 2006. Interviews consisted of open-ended questions on how the participants learned professionalism and what they perceived as challenges to learning professionalism. Two researchers analyzed the interview transcripts for emergent themes by using a grounded-theory approach. RESULTS: Faculty members' and residents' perceptions of how they learned professionalism reflected four major themes: (1) personal values and upbringing, including premedical education experiences, (2) learning by example from professional role models, (3) the structure of the surgery residency, and (4) formal instruction on professionalism. Of these, role modeling was the dominant theme: Participants identified observation, reflection, and reinforcement as playing key roles in their learning from role models and in distinguishing the sometimes blurred boundary between positive and negative role models. CONCLUSIONS: The theoretical framework generated out of this study proposes a focus on specific activities to improve professional education, including an active approach to role modeling through the intentional and explicit demonstration of professional behavior during the course of everyday work; structured, reflective self-examination; and timely and meaningful evaluation and feedback for reinforcement.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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".