Bibliographic record
Abstract
Evidence for Health: From Patient Choice to Global Policy is a practical guide to evidence-informed decision-making. It provides health practitioners and policy-makers with a broad overview of how to improve health and reduce health inequities, as well as the tools needed to make informed decisions that will have a positive influence on health. Chapters address questions such as: What are the major threats to health? What are the causes of poor health? What works to improve health? How do we know that it works? What are the barriers to implementation? What are the measures of success? The book provides an algorithm for arriving at evidence-informed decisions that take into consideration the multiple contextual factors and value judgements involved. Written by a specialist in public health with a wealth of international experience, this user-friendly guide demystifies the decision-making process, from personal decisions made by individual patients to global policy decisions.
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.
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 | 0.041 | 0.188 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.011 | 0.006 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.084 | 0.024 |
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".