The value of head nurse satisfaction survey table in the application of clinical nursing management
Bibliographic record
Abstract
Objective: To investigate the value of nurse satisfaction survey table in the application of clinical nursing management.Methods: Every quarter nurses should complete a self-designed nurse satisfaction survey table,the number of nurses who participated in the survey should ≥90%.Results: The results of survey analysis showed that nurse understood their problems,and effort to correct their defects.The satisfaction in 2008(78.86%) increased significantly than 2010(93.39%),with working hours of capacity increasing,the management,communication skills of nurses increased significantly),with working hours of capacity increasing,the professional and technical capabilities of nurses did not increase.There was no contact between the working hours of capacity and set an example.Conclusion: Head nurse satifaction survey table could find the inadequacies of work,help nurses to strengthen self-construction,improve the overall quality and management capabilities through head nurse satisfaction survey table.
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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 | 0.019 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".