Translating learning into practice: lessons from the practice-based small group learning program.
Bibliographic record
Abstract
UNLABELLED: PROBLEM ADDRESSED The need for effective and accessible educational approaches by which family physicians can maintain practice competence in the face of an overwhelming amount of medical information. OBJECTIVE OF PROGRAM: The practice-based small group (PBSG) learning program encourages practice changes through a process of small-group peer discussion-identifying practice gaps and reviewing clinical approaches in light of evidence. PROGRAM DESCRIPTION: The PBSG uses an interactive educational approach to continuing professional development. In small, self-formed groups within their local communities, family physicians discuss clinical topics using prepared modules that provide sample patient cases and accompanying information that distils the best evidence. Participants are guided by peer facilitators to reflect on the discussion and commit to appropriate practice changes. CONCLUSION: The PBSG has evolved over the past 15 years in response to feedback from members and reflections of the developers. The success of the program is evidenced in effect on clinical practice, a large and increasing number of members, and the growth of interest internationally.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".