Defining the Key Roles and Competencies of the Clinician–Educator of the 21st Century
Bibliographic record
Abstract
PURPOSE: To determine a consensus definition of a clinician-educator and the related domains of competence. METHOD: During September 2010 to March 2011, the authors conducted a two-phase mixed-methods national study in Canada using (1) focus groups of deans of medicine and directors of medical education centers to define the attributes, domains of competence, and core competencies of clinician-educators using a grounded theory analysis, and (2) a survey of 1,130 deans, academic chairs, and residency program directors to validate the focus group results. RESULTS: The 22 focus group participants described being active in clinical practice, applying theory to practice, and engaging in education scholarship-but not holding a particular administrative position-as essential attributes of clinician-educators. Program directors accounted for 68% of the 350 survey respondents, academic chairs for 19%, and deans for 13% (response rate: 31%). Among respondents, 85% endorsed the need for physicians with advanced training in medical education to serve as educational consultants. Domains of clinician-educator competence endorsed by >85% of respondents as important or very important were assessment, communication, curriculum development, education theory, leadership, scholarship, and teaching. With regard to training requirements, 55% endorsed a master's degree in education as effective preparation, whereas 39% considered faculty development programs effective. CONCLUSIONS: On the basis of this study's findings, the authors defined a clinician-educator as a clinician active in health professional practice who applies theory to education practice, engages in education scholarship, and serves as a consultant to other health professionals on education issues.
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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 | 0.032 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".