Digital medical humanities: stage-to-screen lessons from a five year initiative
Bibliographic record
Abstract
Translation of curriculum materials to digital formats has become increasingly common. Medical humanities, typically reliant on human interaction to generate emotional impact, represents an interesting means to study engagement with digitised content. While technology-enhanced learning may provide opportunities to integrate humanities into curricula, redesigning sessions for digital use can be resource intensive and ‘requires consideration of the affordances’ of different media.1 As previously reported in BMJ Medical Humanities , guidance for this process—beyond simply, ‘digitising existing content’—remains limited.1 We present a five year educational case study that outlines our successes and struggles with digitising a medical humanities session for undergraduate medical education. Our model uses, Ed’s Story: the Dragon Chronicles, a verbatim play based exclusively on the journal of a 16 year-old boy with terminal cancer, and 25 interviews conducted after his death with his family, friends and interdisciplinary healthcare team.2 We have described the play’s development and initial curriculum integration elsewhere.2 Concepts of autonomy, interprofessionalism, end of life care, and moral distress were introduced to second year medical students with the play during an oncology block in lieu of a lecture. The session met objectives outlined for both the oncology unit and a longitudinal professional competencies curriculum. A mandatory live viewing (at a theatre venue outside the classroom) received positive feedback.2 To address feasibility challenges, including delivery to distributed sites, subsequent annual sessions employed a digital video disc (DVD.) The DVD was filmed at live performances with audiences present and used multiple camera angles; however, performances and staging were not altered. The in-classroom DVD and postperformance discussions were facilitated by technology-enhanced lecture theatres. Feedback was collected with Research Ethics Board approval using anonymous, web-based …
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".