Waves of attention: patterns and themes of international antimicrobial resistance reports, 1945–2020
Bibliographic record
Abstract
This article uses quantitative and qualitative approaches to review 75 years of international policy reports on antimicrobial resistance (AMR). Our review of 248 policy reports and expert consultation revealed waves of political attention and repeated reframings of AMR as a policy object. AMR emerged as an object of international policy-making during the 1990s. Until then, AMR was primarily defined as a challenge of human and agricultural domains within the Global North that could be overcome via 'rational' drug use and selective restrictions. While a growing number of reports jointly addressed human and agricultural AMR selection, international organisations (IOs) initially focused on whistleblowing and reviewing data. Since 2000, there has been a marked shift in the ecological and geographic focus of AMR risk scenarios. The Global South and One Health (OH) emerged as foci of AMR reports. Using the deterritorialised language of OH to frame AMR as a Southern risk made global stewardship meaningful to donors and legitimised pressure on low-income and middle-income countries to adopt Northern stewardship and surveillance frameworks. It also enabled IOs to move from whistleblowing to managing governance frameworks for antibiotic stewardship. Although the environmental OH domain remains neglected, realisation of the complexity of necessary interventions has increased the range of topics targeted by international action plans. Investment nonetheless continues to focus on biomedical innovation and tends to leave aside broader socioeconomic issues. Better knowledge of how AMR framings have evolved is key to broadening participation in international stewardship going forward.
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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 | 0.035 | 0.133 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.021 | 0.032 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".