Key stakeholder opinions for a national learner education handover
Bibliographic record
Abstract
BACKGROUND: Sharing information about learners during training is seen as an important component supporting learner progression and relevant to patient safety. Shared information may cover topics from accommodation requirements to unprofessional behavior. The purpose of this study was to determine the views of key stakeholders on a proposed national information sharing process during the transition from undergraduate to postgraduate medical education in Canada, termed the Learner Education Handover (LEH). METHOD: Key stakeholder groups including medical students, resident physicians, residency program directors, medical regulatory authority representatives, undergraduate medical education deans, student affairs leaders, postgraduate medical education deans participated in focus groups conducted via teleconference. Data were transcribed and coded independently by two coders, then analyzed for themes informed by principles of constructivist grounded theory. RESULTS: Sixty participants (33 males and 27 females) from 16 focus groups representing key stakeholder groups participated. Most recognized value in a national LEH that would facilitate a smooth learner transition from medical school to residency. Potential risks and benefits of the LEH were identified. Themes significant to the content, process and format of the LEH also emerged. Guiding principles of the LEH process were determined to include that it be learner-centered while supporting patient safety, resident wellness and professional behavior. The learner and representatives from their undergraduate medical education environment would each contribute to the LEH. CONCLUSIONS: The LEH must advocate for the learner with respect for learner privacy, while promoting professionalism, patient safety and learner wellness.
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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 | 0.035 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".