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.
fundA Canadian funder is recorded on the work.
VenueJournal of Development Effectiveness · 2020
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of Saskatchewan
FundersEuropean Social FundNational Institute for Occupational Safety and HealthNational Institute of Child Health and Human DevelopmentNorwegian Institute of Public HealthNIHR Oxford Biomedical Research CentreJapan Society for the Promotion of ScienceNational Health and Medical Research CouncilQatar National Research FundUniversity of North Carolina at Chapel HillGillings School of Public HealthCollege of Pharmacy, University of MichiganNational Institutes of HealthMedical Research CouncilAfrican Academy of SciencesSecretaría Nacional de Ciencia, Tecnología e InnovaciónNational Research University Higher School of EconomicsDeakin UniversityUniversidad de Costa RicaUniversiti Kebangsaan MalaysiaVetenskapsrådetKuwait UniversityAcademy of FinlandMax-Planck-GesellschaftUniversity College DublinPublic Health AgencyConselho Nacional de Desenvolvimento Científico e TecnológicoUniversity of GhanaQueensland GovernmentCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCarolina Population Center, University of North Carolina at Chapel HillFonds National de la Recherche LuxembourgAutoritatea Natională pentru Cercetare StiintificăInstituto de Salud Carlos IIINational Natural Science Foundation of ChinaDepartment of Biotechnology, Ministry of Science and Technology, IndiaComunidad de MadridNational Heart Foundation of AustraliaThe Wellcome Trust DBT India AlliancePeking UniversityNational Research FoundationNational Institute for Health and Care ResearchEuropean CommissionDepartment of Science and Innovation, South AfricaNational Authority for Scientific Research and InnovationPublic Health EnglandXiamen UniversityMinisterio de Ciencia, Innovación y UniversidadesWellcome TrustMinistério da Ciência, Tecnologia e Ensino SuperiorUniversity of CalgaryBundesministerium für Bildung und ForschungBritish Heart FoundationScottish GovernmentEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentBHF Centre of Research Excellence, OxfordNational Institute of Mental HealthDanmarks GrundforskningsfondNational Aeronautics and Space AdministrationNational Institute on AgingAlexander von Humboldt-StiftungFundação para a Ciência e a TecnologiaBill and Melinda Gates FoundationYale UniversityUnited Nations Population FundUnited States Agency for International DevelopmentPublic Health Agency of CanadaBloomberg PhilanthropiesHealth Research Council of New ZealandUniversity of New South WalesMinistero della SaluteQueensland HealthChina Medical UniversityUniversity of Michigan
KeywordsBeneficiaryWastingDietary diversityEnvironmental healthMedicineCross-sectional studyNutrition EducationSocioeconomicsGerontologyGeographyAgriculturePolitical scienceEconomicsFood security
Abstract
fetched live from OpenAlexBRAC Bangladesh trains community health workers to communicate about nutrition in its Maternal, Newborn and Child Health programme. We estimate the programme’s impact on nutrition outcomes among rural Bangladeshi children of two years and younger. We find positive effects on dietary diversity, and show that the programme reduces stunting with 7 percentage points using data from 1600 households in 40 beneficiary mouzas and 40 comparison mouzas. We find larger effects for households where primary caregivers have finished primary school. We did not find effects on wasting, which in contrast to stunting is higher among children with primary caregivers without education.
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 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.
metaresearch head score (Codex)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.514
Codex and Gemma teacher scores by category
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.
Teacher spread0.292 · 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
