Better Care and Better Value for Canadians: A Review of RCT Studies of Nurse Interventions
Bibliographic record
Abstract
An RN credential has been called "a ticket to the world." Canadian RNs have been active participants in migration, especially to the United States. In an increasingly globally oriented world, Canadian nurse graduates have many employment options. The purpose of this study was to explore the job values and expectations of baccalaureate nursing students who indicated they were considering migrating for work abroad for their first job and to explore their confidence in having these values met in Canada compared to another country. This was a quantitative study guided by the Value-Expectancy Framework. Data were collected through a Web-based self-report survey and analyzed using descriptive statistics for sample characteristics and t tests for comparison. Nonprobability convenience sampling of graduating baccalaureate nursing students from a Canadian border region was used. Of 130 respondents, 92 (70.8%) indicated that they were considering migrating from Canada for work. Respondents believed that working abroad would provide more adventure, full-time work, professional development, appropriate staffing, flexible scheduling, and freedom to choose their preferred job sector/specialty. The authors conclude that there is a need to study nursing graduates' labour mobility both within and outside of Canada and the factors that influence their decision-making and to address the factors that encourage them to leave Canada. Human resource planning will become increasingly important given the predicted nursing shortage and changes to nurse licensure in Canada with the potential to influence migration.
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.
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 | 0.025 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".