Interprofessional education for internationally educated health professionals: an environmental scan
Bibliographic record
Abstract
OBJECTIVE: The objective of this environmental scan was to identify Western Canadian interprofessional education (IPE) resources that currently exist for internationally educated health professionals (IEHPs). METHODOLOGY: A web-based search was conducted to identify learning resources meeting defined inclusion criteria with a particular focus on the resources available in the Western Canadian provinces. Information was extracted using a standardized template, and we contacted IEHP programs for additional information if necessary. Members of the research team reviewed preliminary findings, identified missing information from their respective provinces, and contacted organizations to fill in any gaps. RESULTS: The scan identified 26 learning resources for IEHPs in Western Canadian provinces and 15 in other provinces focused on support for IEHPs to meet their profession-specific licensing requirements and to acquire knowledge and competencies relevant to working in the Canadian health care system. Most learning resources, such as those found in bridging programs for IEHPs, included an orientation to the Canadian health care system, components of cultural competence, and at least one aspect of interprofessional competence (eg, communication skills). None of the 41 learning resources provided comprehensive training for IEHPs to cover the six interprofessional competency domains defined in the Canadian Interprofessional Health Collaborative (CIHC) National Interprofessional Competency Framework. CONCLUSION: The IEHPs learning resources in Western Canada do not cover all of the interprofessional competencies. This review points to the value of developing a comprehensive IPE curriculum, based on the six domains identified in the CIHC National Interprofessional Competency Framework.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.023 | 0.046 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".