New beginnings in post graduate medical education. Latin American Medical Education Leaders Forum
Bibliographic record
Abstract
Introduction: The consequences of the Covid-19 epidemic have been catastrophic for Latin America in 2021. This study explores experiences, lessons learned, and practice changes during this critical time in post-graduate medical education in Latin America. Methods: A panel of 53 post-graduate medical education leaders from 8 Latin American countries and Canada was invited to participate in the 2021 Latin American Medical Education Leaders Forum to share their experiences, lessons learned, and main educational practice changes given the Covid-19 pandemic scenario. Participants were selected following a snowball technique with the goal of obtaining a diverse group of experts. Small group discussions were conducted by bilingual facilitators based on a semi-structured questionnaire. The plenary session with the main conclusions of each group was recorded and fully transcribed for a thematic analysis using a framework methods approach. Results: Participants´ profiles included 13 experienced clinician-educators, 19 program directors, and 23 deans or organizational representatives. Seven specific themes emerged. They followed a pattern that went from an initial emotional reaction of surprise to a complex collective response. The responses highlighted the value of adaptability, the application of new digital skills, a renovated residents’ protagonism, the strengthening of humanism in medicine, the openness of new perspectives in wellness, and finally, an unresolved challenge of assessment in medical education in a virtual post-pandemic scenario. Conclusion: A diverse panel of medical educators from Latin America and Canada identified changes triggered by the Covid-19 pandemic that could transform postgraduate medical education in the region.
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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 | 0.003 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".