Downward occupational mobility of baccalaureate‐prepared, internationally educated nurses to licensed practical nurses
Bibliographic record
Abstract
AIM: This study explored the experience of baccalaureate-prepared, internationally educated nurses who work as licensed practical nurses in Canada. BACKGROUND/INTRODUCTION: Internationally educated nurses experience several barriers to workforce integration on arrival in destination countries. Given these barriers, evidence suggests that internationally educated nurses sometimes experience downward occupational mobility and deskilling in destination countries. Some baccalaureate-prepared, internationally educated nurses work as licensed practical nurses in destination countries, but there is minimal research on this population. METHODS: We used an exploratory transnational feminist qualitative research design. Following ethics approval, a total of 14 baccalaureate-prepared, internationally educated nurses who currently or recently worked as practical nurses in Canada were interviewed for the study. Data were thematically analysed with the aide of NVivo 11 data software. RESULTS: Our results revealed four key themes related to the experiences of this group of nurses: they migrate to Canada with hope for a better personal and professional life; they experience barriers to workforce integration as registered nurses and discover an easier path in the licensed practical nurse registration process; they experience deskilling and ambivalent skill recognition; and they feel dissatisfied as a licensed practical nurse in Canada. DISCUSSION/CONCLUSION: There is a need for policy to support the upward mobility of baccalaureate-prepared, internationally educated nurses who work as practical nurses. IMPLICATIONS FOR NURSING POLICY: Implications for policymakers include the need to address the barriers to becoming registered nurses, including application processing times and lack of adequate access to educational programmes.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".