InspirE5: a participatory, internationally informed framework for health humanities curricula in health professions education
Bibliographic record
Abstract
BACKGROUND: Reporting on the effect of health humanities teaching in health professions education courses to facilitate sharing and mutual exchange internationally, and the generation of a more interconnected body of evidence surrounding health humanities curricula is needed. This study asked, what could an internationally informed curriculum and evaluation framework for the implementation of health humanities for health professions education look like? METHODS: The participatory action research approach applied was based on three iterative phases 1. Perspective sharing and collaboration building. 2. Evidence gathering 3. Development of an internationally relevant curriculum and evaluation framework for health humanities. Over 2 years, a series of online meetings, virtual workshops and follow up communications resulted in the production of the curriculum framework. RESULTS: Following the perspective sharing and evidence gathering, the InspirE5 model of curriculum design and evaluation framework for health humanities in health professions education was developed. Five principal foci shaped the design of the framework. ENVIRONMENT: Learning and political environment surrounding the program. Expectations: Graduate capabilities that are clearly articulated for all, integrated into core curricula and relevant to graduate destinations and associated professional standards. EXPERIENCE: Learning and teaching experience that supports learners' achievement of the stated graduate capabilities. EVIDENCE: Assessment of learning (formative and/or summative) with feedback for learners around the development of capabilities. Enhancement: Program evaluation of the students and teachers learning experiences and achievement. In all, 11 Graduate Capabilities for Health Humanities were suggested along with a summary of common core content and guiding principles for assessment of health humanities learning. DISCUSSION: Concern about objectifying, reductive biomedical approaches to health professions education has led to a growing expansion of health humanities teaching and learning around the world. The InspirE5 curriculum and evaluation framework provides a foundation for a standardised approach to describe or compare health humanities education in different contexts and across a range of health professions courses and may be adapted around the world to progress health humanities education.
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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 | 0.218 | 0.082 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.009 | 0.018 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".