Work‐Related Disability in Canadian Nurses
Bibliographic record
Abstract
PURPOSE: To determine factors contributing to high registered nurse (RN) injury claim rates in Canadian hospitals. DESIGN: Cross-sectional study of secondary 1998-99 data for RNs (N = 8,044) in Ontario, Canada, linked at the hospital level (n = 127). METHODS: Descriptive statistics, correlations, and logistic regression analyses were conducted. RESULTS: The odds of a high RN lost-time claim rate increased by 70% for each quartile increase in the percentage of RNs reporting more than 1 hour of overtime per week. The odds of a high RN musculoskeletal lost-time claim rate decreased by 64% for every one unit increase in the hospital-level score on the nurse-physician relationship subscale. CONCLUSIONS: To retain and optimize scarce hospital nursing resources, strategies to address overtime, sick time, and nurse-physician relationships might provide fiscal and human benefits.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".