Work Setting, Community Attachment, and Satisfaction Among Rural and Remote 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
OBJECTIVES: To describe community satisfaction and attachment among rural and remote registered nurses (RNs) in Canada. DESIGN AND SAMPLE: Cross-sectional survey of rural and remote RNs in Canada as part of a multimethod study.The sample consisted of a stratified random sample of RNs living in rural areas of the western country and the total population of RNs who worked in three northern regional areas and those in outpost settings. A subset of 3,331 rural and remote RNs who mainly worked in acute care, long-term care, community health, home care, and primary care comprised the sample. MEASURES: The home community satisfaction scale measured community satisfaction, whereas single-item questions measured work community satisfaction and overall job satisfaction. Community variables were compared across practice areas using analysis of variance, whereas a thematic analysis was conducted of the open-ended questions. RESULTS: Home care and community health RNs were significantly more satisfied with their work community than RNs from other practice areas. RNs who grew up in rural communities were more satisfied with their current home community. Four themes emerged from the open-ended responses that describe community satisfaction and community attachment. CONCLUSIONS: Recruitment and retention strategies need to include mechanisms that focus on community satisfaction, which will enhance job satisfaction.
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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 | 0.001 | 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