Improving Journal Clubs Through the Use of Positive Deviance: A Mixed-Methods Study
Bibliographic record
Abstract
BACKGROUND: Plastic surgery journal clubs are often unsatisfactory for both surgeons and residents, leading to frustration and poor surgeon attendance. OBJECTIVE: To assess and modify journal clubs using the principles of positive deviance. METHODS: Surgeons and residents were surveyed across five domains before and after journal club modification. These included perception of the quality of articles chosen, the quality of the presentations, postpresentation discussions, educational benefit and overall satisfaction. RESULTS: Using the principles of positive deviance, the authors were able to identify points of concern with journal clubs and make suggestions for improvement. Postintervention surveys demonstrated a statistically significant improvement in journal clubs across all five domains assessed. CONCLUSIONS: Using the principles of positive deviance, journal club satisfaction was improved. The interventions presented could be used to improve journal clubs at other institutions. In addition, the principles of positive deviance can be used to address a variety of administrative and educational challenges faced by plastic surgery programs.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".