Bibliographic record
Abstract
Background: Interprofessional collaboration is at the center of much of our work as Neurologists, yet often Medical Education inadequately prepares students for the complexities of interdisciplinary practice. Authentic, meaningful Interprofessional Education (IPE) requires consideration in involement of all individuals involved in interprofessional health care (IPHC) (Holbrook, 2013). Methods: We have collected authentic stories of acute stroke care through interviews with patients and other health care professionals on the acute stroke care team. Drawing on these narratives, we have crafted a multimedia story combining film, photography, and art. Results: This case will be integrated into Western University’s Undergraduate Medical Education curriculum but is intended to be a valuable tool for teaching IPE competencies in all IPE contexts. All media will be available thorugh Western Libaries open access Health Education Media Library. Main learning outcomes include improved recognition of HCP roles and the vital and diverse contributions of each team member. Conclusions: Drawing on the experiences of real stroke patients, families, and all other HCPs, we have crafted a rich educational case portraying the complexity of IPHC that will allow learners to reflect on the complex roles of health professoinals in a successful interprofessional team.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".