Bibliographic record
Abstract
The 1990s brought new fiscal realities to healthcare, leading to nursing job loss estimates in tens of thousands following widespread hospital restructuring to manage costs and improve efficiency. This research aimed at examining (a) how multiple episodes of hospital restructuring leading to layoff of nurses affected nurses who remained employed and (b) whether and how nursing leadership mitigated or intensified the negative effects of hospital restructuring on nurses. This dissertation comprised 3 empirical studies leading to 5 publications. The first study was a systematic literature review; the second and third used structural equation modeling to develop and test theoretical models addressing nursing practice environments and effects of hospital restructuring on nurses. The combined findings in this dissertation illustrate that hospital restructuring had significant negative physical/emotional health effects on nurses who remained employed. Nurses who worked for resonant (emotionally intelligent) leadership reported positive health and well-being, and opportunities to provide quality patient care. Nurses who worked for dissonant leadership reported greater negative effects of hospital restructuring. These findings led to a beginning theory of relational energy--a mechanism of mitigation whereby resonant nursing leaders invest energy into collaborative relationships with nurses, thereby positively influencing health and well-being, and, ultimately, outcomes for patients.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".