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Record W2261365333 · doi:10.5539/jsd.v9n1p187

Health Interventions and Child Health in Sub-Saharan Africa: Assessing the Impact of the Millennium Development Goal

2016· article· en· W2261365333 on OpenAlexvenueno aff
Oluwatomisin Ogundipe, Oluranti Olurinola, Adeyemi Ogundipe

Bibliographic record

VenueJournal of Sustainable Development · 2016
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
Fundersnot available
KeywordsMillennium Development GoalsChild mortalityPsychological interventionBreastfeedingChild healthIntervention (counseling)Proxy (statistics)Environmental healthDeveloping countryEconomic growthInfant mortalityMedicineHealth educationPublic healthPediatricsNursingPopulationEconomics

Abstract

fetched live from OpenAlex

The study investigates the role of health interventions on child health in developing Africa for the period 1990-2013 using a dynamic panel approach. Among others, the study examines the effect of millennium development intervention programme on child health outcomes. Our analysis reveals MDG intervention as extremely pertinent in reducing the incidence of child mortality in Africa. It implies that introduction of MDGs culminates into increasing the rate of child survival in Africa. Similarly, maternal literacy, maternal health and other child protective measures adopted were found to be statistically significant in improving child health outcomes. The proportion of under-five mortality (proxy for child health) responds more strongly and negatively to immunization coverage, exclusive breastfeeding and DPT vaccines. On the other hand, the quality of institution contributively impact under-five mortality in Africa. Finally, there is need to strengthen institutional arrangement, ensure compulsory basic education for women and strengthen the health system to achieve full packages of intervention, curtain the rising incidence of child deaths and attain the MDGs.

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 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)0.000
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: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.020
GPT teacher head0.320
Teacher spread0.300 · 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 teacher head, 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

Citations8
Published2016
Admission routes1
Has abstractyes

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