The World Health Organization and the Globalization of Chronic Noncommunicable Disease
Bibliographic record
Abstract
Chronic noncommunicable diseases (NCDs) in low‐ and middle‐income countries have recently provoked a surge of public interest. This article examines the policy literature—notably the archives and publications of the World Health Organization (WHO), which has dominated this field—to analyze the emergence and consolidation of this new agenda. Starting with programs to control cardiovascular disease in the 1970s, experts from Eastern and Western Europe had by the late 1980s consolidated a program for the prevention of NCD risk factors at the WHO. NCDs remained a relatively minor concern until the collaboration of World Bank health economists with WHO epidemiologists led to the Global Burden of Disease study that provided an “evidentiary breakthrough” for NCD activism by quantifying the extent of the problem. Soon after, WHO itself, facing severe criticism, underwent major reform. NCD advocacy contributed to revitalizing WHO's normative and coordinative functions. By leading a growing advocacy coalition, within which The Lancet played a key role, WHO established itself as a leading institution in this domain. However, ever‐widening concern with NCDs has not yet led to major reallocation of funding in favor of NCD programs in the developing world.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".