Marching on the Road to Quality: Army Public Health Experience Adopting NACCHO's Roadmap to a Culture of Quality Framework
Bibliographic record
Abstract
The US Army Public Health Center (APHC) adopted the National Association of County and City Health Officials' (NACCHO) Roadmap to a Culture of Quality (CoQ) Improvement framework to define its current culture and adapted the NACCHO's Organizational CoQ Self-Assessment Tool for applicability to a federal agency and workforce. More than 500 Civilian and Military personnel completed the self-assessment in October 2017. The results indicated that the APHC was categorized in the third of six total phases of the NACCHO's Roadmap to a CoQ (Phase 3: Informal or Ad Hoc QI Activities), which generated 13 transitional strategies to advance the APHC toward a CoQ. The APHC demonstrated that a federal public health organization can use and apply results from currently available self-assessment tools and frameworks related to a CoQ. By doing so, the APHC is optimizing its ability to ensure America's Soldiers and the Army Family receive essential and effective public health services.
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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 | 0.031 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".