Cross-sectoral synergy governance programme for antimicrobial resistance control in China using a ‘One Health’ approach: study protocol for a mixed-methods study
Bibliographic record
Abstract
INTRODUCTION: Antimicrobial resistance (AMR) is a critical global public health concern, particularly acute in rural China. Counties, which cover extensive rural regions, face major challenges in AMR governance and thus require priority attention. Yet, AMR governance efforts across sectors are fragmented, with notable gaps in translating policy objectives into sustainable, practical governance measures. This programme will entail a series of studies focusing on county-level cross-sectoral synergy governance for AMR, aiming to identify optimal synergy governance strategies to curb AMR. METHODS AND ANALYSIS: The study comprises three phases: (1) understanding and exploring the state of cross-sectoral synergy governance and its internal mechanisms; (2) empirically evaluating AMR synergy governance capability using a developed evaluation indicator tool; and (3) identifying optimal AMR synergy governance strategies through a simulation and prediction model. Phase I involves conducting a content analysis of policy documents and semistructured interviews to understand and explore the state of cross-sectoral synergy governance and internal mechanisms. An evaluation indicator tool for AMR synergy governance capability will be developed through a two-round modified Delphi survey, hierarchical analysis process and percentage weighting method, with a typical case analysis being used for empirical evaluation in phase II. Phase III entails developing a simulation and prediction model using a series of artificial intelligence technologies, such as distributed Scrapy crawler technology, large language models, generative adversarial networks and deep multilayer models, all aimed at identifying optimal AMR synergy governance strategies. ETHICS AND DISSEMINATION: This study was approved by the ethics committee of the Centre for Health Management and Policy Research, Shandong University (No. ECSHCMSDU20240904). The results of the studies will be submitted for publication in peer-reviewed journals, presented at national and international academic conferences.
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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 | 0.051 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.047 | 0.006 |
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".