Overview of social inequalities in health in the Region of the Americas, using various methodological approaches
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Bibliographic record
Abstract
Over the past decade, according to several important indicators, health conditions have improved in the Region of the Americas. However, inequalities persist among the countries of the Region. This article has two primary objectives: 1) to provide some unbiased evidence on health inequalities among countries of the Region of the Americas and 2) to illustrate the application of some of the more frequently used methods for measuring inequalities, including effect measurements, population attributable risk, the slope index of inequality, the relative index of inequality, and the concentration index. Analyses have shown that there are great health disparities in the Region of the Americas. For example, residents of the poorest countries of the Region live nearly 10 years less, on average, than do residents of the richest countries. If the other countries of the Americas had the same incidence of tuberculosis as does the subregion of North America (Bermuda, Canada, and the United States of America), there would be 76% fewer cases of this disease in the Region. In the Americas, nearly 35% of deaths of infants under 1 year old are concentrated in the 20% of live births that occur in the group with the lowest income. As for maternal mortality in the Americas, fewer than 2% of maternal deaths occur in association with the 20% of live births in the group with the highest income. The analyses of health inequalities based on the use of various methods highlight the existence of important disparities among subregions and countries of the Americas that are not readily seen when using only the more-traditional methods for analyzing mortality and morbidity. There is also a need to incorporate the concepts of distribution and socioeconomic dimensions of health when interpreting a given situation. Using this approach will allow decisionmakers to target areas and populations that are in less-favorable conditions. A considerable body of aggregate data at the Regional and country levels from routine information systems is already available--especially on morbidity, mortality, and other health-related factors--that can be used on a regular basis to analyze health inequalities. These kinds of analyses may be regarded as a first step toward the identification of health inequities.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it