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Record W2321311939 · doi:10.1177/1090198115606918

The Global Epidemiologic Transition

2016· article· en· W2321311939 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Education & Behavior · 2016
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEpidemiological transitionContext (archaeology)Relevance (law)Global healthPublic healthNutrition transitionEnvironmental healthConstruct (python library)Paradigm shiftMedicineDiseaseBurden of diseaseTransition (genetics)GerontologyEconomic growthPolitical scienceGeographyPopulationComputer scienceObesityPathology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.594
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.388
GPT teacher head0.544
Teacher spread0.155 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it