Job satisfaction among a multigenerational nursing workforce
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
AIM: To explore generational differences in job satisfaction. BACKGROUND: Effective retention strategies are required to mitigate the international nursing shortage. Job satisfaction, a strong and consistent predictor of retention, may differ across generations. Understanding job satisfaction generational differences may lead to increasing clarity about generation-specific retention approaches. METHOD: The Ontario Nurse Survey collected data from 6541 Registered Nurses. Participants were categorized as Baby Boomer, Generation X or Generation Y based on birth year. Multivariate analysis of variance explored generational differences for overall and specific satisfaction components. RESULTS: In overall job satisfaction and five specific satisfaction components, Baby Boomers were significantly more satisfied than Generations X and Y. CONCLUSION: It is imperative to improve job satisfaction for younger generations of nurses. IMPLICATIONS FOR NURSING MANAGEMENT: Strategies to improve job satisfaction for younger generations of nurses may include creating a shared governance framework where nurses are empowered to make decisions. Implementing shared governance, through nurse-led unit-based councils, may lead to greater job satisfaction, particularly for younger nurses. Opportunities to self schedule or job share may be other potential approaches to increase job satisfaction, especially for younger generations of nurses. Another potential strategy would be to aggressively provide and support education and career-development opportunities.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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