Society for Academic Continuing Medical Education Intervention Guideline Series
Bibliographic record
Abstract
The Society for Academic Continuing Medical Education commissioned a study to clarify and, if possible, to standardize the terminology for a set of important educational interventions. In the form of a guideline, this article describes one such intervention, interprofessional education (IPE), which is a common intervention in health professions education. IPE is an opportunity for individuals of multiple professions to interact to learn together, to break down professional silos, and to achieve interprofessional learning outcomes in the service of high-value patient care. Based on a review of recent evidence and a facilitated discussion with US and Canadian experts, we describe IPE, its terminology, and other important information about the intervention. We encourage leaders and researchers to consider and to build on this guideline as they plan, implement, evaluate, and report IPE efforts. Clear and consistent use of terminology is imperative, along with complete and accurate descriptions of interventions, to improve the use and study of IPE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.014 | 0.009 |
| Insufficient payload (model declined to judge) | 0.030 | 0.020 |
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".