The changing profile of the internationally educated nurse workforce: Post-pandemic implications for health human resource planning
Bibliographic record
Abstract
As part of its post COVID-19 recovery plan, the Canadian government is increasing the number of skilled immigrants, including Internationally Educated Nurses (IENs). However, pre-pandemic data show that IENs are underutilized and underemployed despite their education and experience. Focusing on the province of Ontario, this article explores trends in the IEN workforce and policies to address the nursing shortage. Barriers to IEN integration are reviewed and changes in the demographic and employment characteristics of IENs are analyzed. The disproportionate number of IENs employed in the Ontario long-term care sector, which has low wages and poor working conditions, emphasizes the need for policies that support the integration of IENs into the broader Canadian health system and increase their earning potential. To engage in strategic workforce planning and policy development, health leaders require access to nurse demographic and employment data that is timely and reflects the international and domestic labour supply.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".