Understanding the determinants of anemia reduction among women of reproductive age: Exemplar country case studies’ methodology
Bibliographic record
Abstract
BACKGROUND: Since 2000, only a few countries have substantially reduced the burden of anemia among women 15-49 y of age. The Exemplars in Anemia Reduction among Women of Reproductive Age (WRA) studied the determinants of success among these countries. OBJECTIVES: To describe the methodology used to determine the factors associated with anemia reduction in high-performing countries, with the aim to guide policy and programmatic decisions in other countries with similar sociodemographic and health indices. METHODS: This article describes the process used to identify countries with exemplary reduction in WRA anemia burden, compared with their peers. We describe the Exemplars in Global Health methodology, the mixed-methods approach used to identify and quantify the macro- and microlevel characteristics associated with anemia burden decline among WRA. Quantitative analyses include descriptive and equity analyses, multivariate linear regression, and Oaxaca-Blinder decomposition analysis. Qualitative analyses include in-depth interviews and focus group discussions with national, subnational, and community stakeholders, as well as review of programs and policies with the potential to impact women's health and/or nutrition, enacted in the countries over the last 20 y. A technical advisory group oversaw all research activities. RESULTS: We identified 5 countries, namely, Mexico, Pakistan, Philippines, Uganda, and Senegal, as anemia exemplars, after considering the magnitude of anemia decline between 2000 and 2018, availability of ≥2 nationally representative anemia surveys, geographical diversity to account for the complex etiology of anemia, regional representation, and logistics of in-country work. CONCLUSIONS: Exemplars in Anemia Reduction among WRA seeks to create awareness of how little anemia prevalence has changed globally and aims to inform and spur global efforts for improving women's health and nutrition.
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 | 0.027 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".