LPN Perspectives of Factors that Affect Nurse Mobility in Canada
Bibliographic record
Abstract
Although the licensed practical nurse (LPN) workforce represents an ever-growing and valuable human resource, very little is known about reasons for practical nurse mobility. The purpose of this study was to describe LPN perspectives regarding motives for inter-provincial/territorial (P/T) movement in Canada. Participants included 200 LPNs from nine P/T, and data were analyzed using a qualitative descriptive approach. Three primary themes were identified regarding motivators for LPN migration, including (a) scope of practice, (b) education and advancement opportunities and (c) professional respect and recognition. Although current economic forces have a strong influence on nurse mobility, these findings emphasize that there are other equally important factors influencing LPNs to move between jurisdictions. As such, policy makers, administrators and researchers should further explore and address these themes in order to strengthen Canada's nursing workforce.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".