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
Non-communicable diseases (NCDs) are the leading cause of death worldwide, contributing to over 73% of all deaths annually. Each day NCDs cause more than 100,000 deaths, 80% of which occur in low- and middle-income countries. NCDs, however, are largely preventable, and a great deal of technical knowledge exists about how to prevent and manage them. Why, then, have we, as a global community, not been more successful at reducing this NCD burden? Does a universal problem not have a universal solution? Created by an international consortium of experts, this informative and accessible book provides practical guidelines, key learning points, and dynamic, real-world case studies to aid NCD program managers, policy officers and decision-makers in low- and middle-income countries, so that they can assess interventions for the prevention and control of NCDs. The book was commissioned by the Prince Mahidol Award Conference (PMAC), an annual international conference centred on policy of global significance related to public health. NCD Prevention: Best Buys, Wasted Buys and Contestable Buys emphasises the importance of context in NCD control and prevention, arguing that the success of an intervention lies in an ability to respond to local needs and environments. The book comprises ten chapters, which collectively explore the reasons behind, and strategies for, preventing and managing the NCD burden. It spans key themes such as political economy, the transferability of economic evidence, the role of cross-sectoral policies, the importance of deliberative processes, and health technology assessment. This book is written for the benefit of the global health community, and is primarily targeted at those individuals who are involved in NCD programs. This book will also be of interest to NCD champions, policy advocates, and educators spearheading the movement for increased visiblity of NCDs.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it