The <i>Climate Wise</i> slides: An evaluation of planetary health lecture slides for medical education
Bibliographic record
Abstract
Educational Challenge There is an urgent need for innovations in planetary health medical education. Physicians must be prepared to provide high-value, low-carbon healthcare for patients increasingly impacted by the health consequences of climate change.Proposed Solution The Climate Wise slides, an evidence-based, open-access pedagogical tool that provides didactic planetary health medical education organized by medical subspecialty, was developed and evaluated by a virtual lecture session that presented a subset of the slides to N = 75 Canadian medical students. Each participant completed a questionnaire before and after the Climate Wise virtual lecture that included multiple choice questions to assess their planetary health knowledge and a rating of their interest in including the Climate Wise slides in medical curricula.Lessons Learned Participants showed significantly improved planetary health knowledge scores (p < 0.0001) and increased interest in including the Climate Wise slides in medical curricula (p < 0.001) after the virtual Climate Wise lecture session. This study demonstrates that the Climate Wise slides are a valuable pedagogical tool to advance planetary health medical education.Next Steps Future directions include evaluating faculty perspectives on the Climate Wise slides, learning outcomes of the slides implemented longitudinally in medical curricula, and developing higher-order problem-based and simulation-based planetary health medical education resources. Given the urgent need for planetary health medical education, we recommend the global sharing of teaching resources to facilitate the rapid upscaling of validated pedagogical tools internationally.
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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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".