Unpacking “two-way” workplace integration of internationally educated nurses
Bibliographic record
Abstract
This paper presents findings from a qualitative case study that explored long term integration of internationally educated nurses in an Ontario healthcare facility. Using critical social theory as the philosophical underpinnings for this research, we selected the case based on the hospital’s history of employing and supporting internationally educated professionals. Data sources included: documents review, twenty-eight interviews, socio-demographic survey and five focus groups involving IENs and other stakeholders. An overarching theme points to a ‘two-way’ notion of workplace integration whereby efforts are required on the part of the employer as well as the IENs. An in-depth analysis of the data reveals sub-processes of two-way integration: respecting diversity and difference, adopting inclusive practices and striving to achieve equity. Challenges in achieving two-way integration are discussed. Implications for nursing leaders to tap into IENs’ diverse talents for the benefit of their local healthcare systems are highlighted.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".