Florida's Community Hospitals: Service Delivery Choices and Policy Implications
Bibliographic record
Abstract
During the past quarter century, efforts have been made to control rising hospital costs, which are the largest component of U.S. health care expenditures. The purpose of this research is to examine the relationship among five community characteristics and hospital ownership types; determine whether there are differences in operational performance (cost and efficiency) between private nonprofit and private for-profit hospitals; and propose an answer to the question - Why do local governments contract-manage their hospital operation? Using a mixed-method research design, the findings are: (1) there are mixed results in the relationship between community characteristics and hospital ownership types; (2) there are no significant differences in operational performance of private nonprofit and private for-profit hospitals; and (3) hospitals pursue contract management services to gain hospital management expertise, financial management, medical and information technology, and human resource management and recruitment. The implications of this study calls for a broader examination of operational performance among hospital ownership types and policy direction on the goals and mission of a public private venture such as contract management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 source (direct Gemma or distilled Codex), 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".