From margins to mainstream: Incorporating internationally educated health professionals’ skills into primary care
Bibliographic record
Abstract
This case study explores the collaborative integration of Internationally Educated Healthcare Professionals (IEHPs) into comprehensive primary care through partnerships between non-profit organizations and health systems actors. It addresses the critical need for such collaboration amidst challenges of limited access to primary care and underutilization of IEHPs' skills in the Canadian healthcare workforce. Through the examination of ACCES Employment's integration into the Team Primary Care initiative, this article demonstrates the importance of coordinated efforts in overcoming longstanding barriers faced by IEHPs. Data collection involved a review of program activities, program reports, policy documents, and interviews with key collaborators to highlight strategies, partnerships, and outcomes. Data were analyzed to identify recurring patterns in collaborative integration efforts. The initiative reveals promising outcomes in facilitating IEHPs' transition into various healthcare roles through increasing collaboration between non-profit workforce development organizations and health systems actors.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.013 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.025 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".