Who is driving continuing medical education for family medicine?
Bibliographic record
Abstract
INTRODUCTION: Considerable time and money are invested in continuing medical education (CME) for family physicians (FPs) but the effectiveness is uncertain. The participation of FPs as coordinators and teachers is not well known. The goal of this project was to describe the role of FPs in organizing and teaching CME events that are accredited for FPs. METHODS: Information about accredited CME events occurring in Alberta and Nova Scotia was requested from universities, provincial chapters of the College of Family Physicians of Canada, and pharmaceutical companies. Location, coordinating site, organizing committee members, teaching faculty, and format were recorded from each event. The number and proportion of FPs involved in both organizing and teaching CME events accredited for FPs were calculated and compared. RESULTS: A total of 314 CME events were collected, comprising a total of 1,472 hours of CME. From the CME events collected, there were 1,730 organizing committee members and 1,647 teachers. FPs constitute 59% of the organizing committees and 17% of the teachers. Significant differences in the numbers of FP planners and teachers were related to organizing group, format, location, and expected audience composition. DISCUSSION: The accreditation requirement for FPs on organizing committees likely helps preserve a reasonable proportion of FP organizers but not teachers in FP CME. The proportions of true FP planners and teachers may actually be lower than planning documents indicate. Low level of family physician teachers in CME may be due to FPs' not selecting FP teachers, the FP teaching pool's being inadequate, or the organizing committee's being unaware of FPs who are knowledgeable in particular areas.
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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 | 0.006 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".