British Columbia Interprofessional Model for Simulation-Based Education in Health Care
Bibliographic record
Abstract
The rapid uptake of simulation-based education has led to the development of simulation programs and centers all around the world. Unfortunately, many of these centers are functioning as localized silos and not taking advantage of the potential for collaboration with other regional centers to promote interprofessional education. In the province of British Columbia (BC), Canada, 38 institutions, including health care authorities, universities, colleges, and other health-related organizations, have participated in assessing the use of simulation in BC and in developing a provincial model that enables collaboration and interprofessional learning at the provincial level.This article describes methods and results of a needs assessment and discusses an interprofessional simulation in health care educational model that provides access for all health care professionals in BC regardless of their geographic location and/or institutional affiliation. We anticipate that this information will be useful to and supportive of others in developing simulation collaborations in their respective regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".