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Record W2598702482 · doi:10.5325/jafrideve.18.2.0041

Economic Growth, Health Care Reform, and Child Nutrition in Ghana

2016· article· en· W2598702482 on OpenAlexaff
Jemima A. Frimpong, Dozie Okoye, Roland Pongou

Bibliographic record

VenueJournal of African Development · 2016
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of OttawaDalhousie University
Fundersnot available
KeywordsWastingUnderweightMalnutritionEconomicsFellDeveloping countryMedicineDevelopment economicsEconomic growthGeographyBody mass index

Abstract

fetched live from OpenAlex

Policymakers have long argued that economic growth in developing countries will positively impact child health. We examine child nutrition in Ghana during the economic growth of the 1980s and 1990s. We find that stunting in children aged 2-35 months declined from 30% in 1988 to 21% in 1998, but increased to 27% in 2003. Wasting followed an opposite path, while underweight gradually fell from 30% to 24% during this period. We show that these different responses to economic growth reflect differences in the factors generating these outcomes. Improvement in underweight was consistent with the positive household effects of macroeconomic growth, but increase in stunting after 1998 responded to the decline in health care utilization following the reform of the health care system. Indeed, the increased negative impact of a lack of access to healthcare explains most of the decline in child linear growth. The fraction of children presenting any of the three forms of malnutrition remained stable at around 40% during this period. These findings indicate that appropriate policies are needed to ensure that economic growth leads to an improvement in child well-being.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.244
Teacher spread0.235 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2016
Admission routes1
Has abstractyes

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