The influence of job and community satisfaction on retention of public health nurses in rural British Columbia.
Bibliographic record
Abstract
Despite persistent issu e s in retaining nurses, th ere h a s been little research on retaining C anadian rural nurses.This research fo cu ses on the retention of public health n u rses living in largely rural regions of British Columbia.R esearch from the United S tates found that both community and job satisfaction are important in retention of rural public health nurses.T he purpose of this study w as to exam ine; 1) public health n u rse s' satisfaction with their nursing practice and community, and 2) the relationship of public health n u rse s' job satisfaction and community satisfaction to their decisions to stay in their current jobs.A mailed survey with two mailed follow up rem inders w as sen t to all public health n u rses' em ployed by health authorities in eight predom inately rural health regions in British Columbia.This produced 124 re sp o n se s (76% resp o n se rate) for d ata analysis.Both descriptive and inferential statistical an aly ses w ere u sed to interpret th e data.This interpretation w as supplem ented by the public health n u rses' written resp o n ses explaining why they would stay or leave their current employment.This sam ple of public health n u rses w as m ost satisfied with their professional status, professional interaction and their autonom y.They w ere least satisfied with their salary.There w as no significant difference betw een rural and non-rural public health n u rse s' perceived satisfaction with their practice.Public health n u rses w ere m ost satisfied with their com m unities' accep tan ce of their partners, friendliness of the community and their friends.The public health n u rses rated their community satisfaction higher than their job satisfaction.There C h a p te r T h ree -M e th o d s ..............................................
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".