Turnover and vacancy rates for registered nurses
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
BACKGROUND: Turnover of nursing staff is a significant issue affecting health care cost, quality, and access. In recent years, a worldwide shortage of skilled nurses has resulted in sharply higher vacancy rates for registered nurses in many health care organizations. Much research has focused on the individual, group, and organizational determinants of turnover. Labor market factors have also been suggested as important contributors to turnover and vacancy rates but have received limited attention by scholars. PURPOSE: This study proposes and tests a conceptual model showing the relationships of organization-market fit and three local labor market factors with organizational turnover and vacancy rates. METHODS: The model is tested using ordinary least squares regression with data collected from 713 Canadian hospitals and nursing homes. RESULTS: Results suggest that, although modest in their impact, labor market and the organization-market fit factors do make significant yet differential contributions to turnover and vacancy rates for registered nurses. IMPLICATIONS: Knowledge of labor market factors can substantially shape an effective campaign to recruit and retain nurses. This is particularly true for employers who are perceived to be "employers-of-choice."
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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) | 0.000 | 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