Bibliographic record
Abstract
Globally, there has been a shift in the causes of illness and death from infectious diseases to noncommunicable diseases. This changing pattern has been attributed to the effects of an (ongoing) epidemiologic transition. Although researchers have applied epidemiologic transition theory to questions of global health, there have been relatively few studies exploring its relevance especially in the context of emerging allergic disorders in sub-Saharan Africa (SSA). In this article, we address the growing burden of noncommunicable diseases in sub-Saharan Africa through the lens of epidemiologic transition theory. After a brief review of the literature on the evolution of the epidemiologic transition with a particular emphasis on sub-Saharan Africa, we discuss existing frameworks designed to help inform our understanding of changing health trends in the developing world. We subsequently propose a framework that privileges "place" as a key construct informing our understanding. In so doing, we use the example of allergic disease, one of the fastest growing chronic conditions in most parts of the 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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".