Bibliographic record
Abstract
Objective To document the scope of the teaching and evaluation of ethics and professionalism in Canadian family medicine postgraduate training programs, and to identify barriers to the teaching and evaluation of ethics and professionalism. Design A survey was developed in collaboration with the Committee on Ethics of the College of Family Physicians of Canada. The data are reported descriptively and in aggregate. Setting Canadian postgraduate family medicine training programs. Participants Between June and December of 2008, all 17 Canadian postgraduate family medicine training programs were invited to participate. Main outcome measures The first part of the survey explored the structure, resources, methods, scheduled hours, and barriers to teaching ethics and professionalism. The second section focused on end-of-rotation evaluations, other evaluation strategies, and barriers related to the evaluation of ethics and professionalism. Results Eighty-eight percent of programs completed the survey. Most respondents (87%) had learning objectives specifically for ethics and professionalism, and 87% had family doctors with training or interest in the area leading their efforts. Two-thirds of responding programs had less than 10 hours of scheduled instruction per year, and the most common barriers to effective teaching were the need for faculty development, competing learning needs, and lack of resident interest. Ninety-three percent of respondents assessed ethics and professionalism on their end-of-rotation evaluations, with 86% assessing specific domains. The most common barriers to evaluation were a lack of suitable tools and a lack of faculty comfort and interest. Conclusion By far most Canadian family medicine postgraduate training programs had learning objectives and designated faculty leads in ethics and professionalism, yet there was little curricular time dedicated to these areas and a perceived lack of resident interest and faculty expertise. Most programs evaluated ethics and professionalism as part of their end-of-rotation evaluations, but only a small number used novel means of evaluation, and most cited a lack of suitable assessment tools as an important barrier.
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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 | 0.013 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".