Having a Bad Day Is Not an Option: Learner Perspectives on Learner Handover
Bibliographic record
Abstract
PURPOSE: Learner handover is the sharing of learner-related information between supervisors involved in their education. The practice allows learners to build upon previous assessments and can support the growth-oriented focus of competency-based medical education. However, learner handover also carries the risk of biasing future assessments and breaching learner confidentiality. Little is known about learner handover's educational impact, and what is known is largely informed by faculty and institutional perspectives. The purpose of this study was to explore learner handover from the learner perspective. METHOD: Constructivist grounded theory was used to explore learners' perspectives and beliefs around learner handover. Twenty-nine semistructured interviews were completed with medical students and residents from the University of Ottawa and University of California, San Francisco. Interviews took place between April and December 2020. Using the constant comparative approach, themes were identified through an iterative process. RESULTS: Learners were generally unaware of specific learner handover practices, although most recognized circumstances where both formal and informal handovers may occur. Learners appreciated the potential for learner handover to tailor education, guide entrustment and supervision decisions, and support patient safety, but worried about its potential to bias future assessments and breach confidentiality. Furthermore, learners were concerned that information-sharing may be more akin to gossip rather than focused on their educational needs and feared unfair scrutiny and irreversible long-term career consequences from one shared mediocre performance. Altogether, these concerns fueled an overwhelming pressure to perform. CONCLUSIONS: While learners recognized the rationale for learner handover, they feared the possible inadvertent short- and long-term impact on their training and future careers. Designing policies that support transparency and build awareness around learner handover may mitigate unintended consequences that can threaten learning and the learner-supervisor relationship, ensuring learner handover benefits the learner as intended.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".