Bibliographic record
Abstract
OBJECTIVES: This study was undertaken to test the applicability of using a standardized questionnaire for measuring public health nurse (PHN) job satisfaction and to determine whether or not scores changed over 30 months. The importance of establishing a method for ongoing measurement of PHN job satisfaction was underscored by changing directions in practice and an emphasis on building public health capacity. METHOD: A 30-month interval, repeated measures descriptive survey design was used. SAMPLE: A randomly selected sample of 87 PHNs employed within 1 Canadian regional health authority participated. MEASUREMENT: The survey questionnaire, the Index of Worklife Satisfaction, was designed to measure the importance of and satisfaction with 6 components of job satisfaction. RESULTS: Pay and autonomy were the most important components; the order of the 4 remaining components changed from first to second surveys. Professional status, autonomy, and interaction were the most satisfying components; PHN satisfaction with professional status and interaction improved significantly over 30 months. A majority of subjects reported that direct client care/client response/making a difference were worklife aspects providing them with most satisfaction. CONCLUSIONS: A valid, reliable questionnaire suitable for ongoing measurement was tested with PHNs, and baseline levels of their job satisfaction were established.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".