Grade pending: Lessons for hospital quality reporting from the <scp>N</scp>ew <scp>Y</scp>ork <scp>C</scp>ity restaurant sanitation inspection program
Bibliographic record
Abstract
Public quality reporting programs have been widely implemented in hospitals in an effort to improve quality and safety. One such program is Hospital Compare, Medicare's national quality reporting program for US hospitals. The New York City sanitary grade inspection program is a parallel effort for restaurants. The aims of Hospital Compare and the New York City sanitary inspection program are fundamentally similar: to address a common market failure resulting from consumers' lack of information on quality and safety. However, by displaying easily understandable information at the point of service, the New York City sanitary inspection program is better designed to encourage informed consumer decision making. We argue that this program holds important lessons for public quality reporting of US hospitals.
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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 | 0.043 | 0.198 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".