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
Purpose This paper aims to briefly describe the increasingly complex array of organizations influencing American healthcare‐associated infection (HAI) prevention efforts during the modern era of infection control. Design/methodology/approach This paper is a narrative review. Findings The modern era of hospital infection control began in the 1950s, but received relatively little publicity until the dawn of the twenty‐first century. Since then, there has been a wave of unprecedented magnitude in individual state legislation mandates followed by a shift from state to federal agency activity. The resulting programs are in varying stages of development, ability, sustainability, and coordination. Practical implications Many government and healthcare entities are in uncharted territory with this new area of activity, facing challenges in having to coordinate work with many new and unfamiliar partners. Perspectives explored in this part of the Universities Council Symposium help by mapping out the various stakeholders in order to foster a research agenda through better understanding of powerful political players and their influence. Originality/value This is one of the first efforts to describe and map the evolving range of state and federal forces influencing hospitals' efforts to prevent healthcare‐associated infections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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