Staffing-Related Deficiency Citations in Nursing Homes
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
There is evidence that staffing characteristics influence quality of care in nursing homes. Federal and state surveyors conduct inspections of homes to assess their compliance with regulatory standards, including requirements related to staffing. Deficiency citations are issued when these standards are not met. This article examines the relationship between operational, facility, and market characteristics and organizational performance measured as staffing-related deficiency citations. Online Survey Certification of Automated Records (OSCAR) data from 2000 through 2007 were used with multinomial logistic regression analyses to identify factors associated with deficiency citations for staffing. Chain members and facilities with poor quality of care were more likely to receive deficiency citations for staffing. Greater bed count and competition between nursing homes were associated with a decreased likelihood of deficiency citations for staffing. Staffing-related deficiencies within nursing homes vary according to various operational, facility, and market characteristics.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 it