Challenging perceptions about rural practice using narratives: a living library approach in medical education
Bibliographic record
Abstract
Introduction: The shortage of physicians in rural Canada is a continuing challenge. Canadian medical schools have adapted strategies to increase the supply of rural physicians. This study appraises the effectiveness of the living library (also called Human Library©) in medical education, as an avenue for medical and pre-medical students to engage in dialogue with rural health professionals. Similar to a conventional library, readers check out books, except that "books" are human volunteers willing to share relevant personal experiences, and "readers" are the learners. The reading is the personal interaction between human books and students through narratives of experiences. The program "The Library of Life-Stories of Rural Medicine" (TLoL), was developed to provide students with better understanding of rural life and practice through narratives. Methods: This is a mixed methods study, using pre- and post-event surveys. Statistical comparisons were done using Wilcoxon and McNemar's tests. Thematic analysis was used to explore students' expectations of TLoL and to describe their experience and key takeaways. Results: = 0.001). Themes from students' motivations for participation were: (i) students' curiosity, interest, and (ii) their willingness to engage in dialogue with the human books. Themes from the key takeaways were that TLoL allowed students: (i) to walk in a rural professional's shoes, enabling them to see "rural" in a new light, and (ii) to self-reflect and gain a sense of personal growth. Conclusion: Students made gains in attitudes and perceptions toward rural practice. Narratives have the power to challenge held beliefs around rural practice and life, and can encourage students to consider things that traditional medical teaching may not. TLoL can be an effective learning modality in medical education to provide information about rural medicine, in combination with learning opportunities such as rural block rotations and longitudinal clinical clerkship immersions.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".