International nurse migration: U‐turn for safe workplace transition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Increasing globalization of the nursing workforce and the desire for migrants to realize their full potential in their host country is an important public policy and management issue. Several studies have examined the challenges migrant nurses face as they seek licensure and access to international work. However, fewer studies examine the barriers and challenges internationally educated nurses (IEN) experience transitioning into the workforces after they achieve initial registration in their adopted country. In this article, the authors report findings from an empirically grounded study that examines the experience of IENs who entered Ontario's workforce between 2003 and 2005. We found that migrant nurses unanimously described nursing as 'different' from that in their country of origin. Specifically, IENs reported differences in the expectations of professional nursing practice and the role of patients and families in decision-making. In addition, problems with English language fluency cause work-related stress and cognitive fatigue. Finally, the experience of being the outsider is a reality for many IENs. This study provides important insights as policy and management decision-makers balance the tension between increasing the IEN workforce and the delivery of safe patient care.
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.
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 | 0.001 | 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) | 0.000 | 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 it