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Record W2559088806 · doi:10.1186/s12889-016-3840-0

Integrated agriculture programs to address malnutrition in northern Malawi

2016· article· en· W2559088806 on OpenAlexafffund
Rachel Bezner Kerr, Emmanuel Chilanga, Hanson Nyantakyi‐Frimpong, Isaac Luginaah, Esther Lupafya

Bibliographic record

VenueBMC Public Health · 2016
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsWestern UniversityThe Scarborough HospitalUniversity of Toronto
FundersInternational Development Research CentreMcKnight Foundation
KeywordsBiostatisticsMedicineMalnutritionPublic healthEnvironmental healthAgricultureEpidemiologyNursingGeographyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: In countries where the majority of undernourished people are smallholder farmers, there has been interest in agricultural interventions to improve nutritional outcomes. Addressing gender inequality, however, is a key mechanism by which agriculture can improve nutrition, since women often play a crucial role in farming, food processing and child care, but have limited decision-making and control over agricultural resources. This study examines the approaches by which gender equity in agrarian, resource-poor settings can be improved using a case study in Malawi. METHODS: A quasi-experimental design with qualitative methods was used to examine the effects of a participatory intervention on gender relations. Thirty married couple households in 19 villages with children under the age of 5 years were interviewed before and then after the intervention. An additional 7 interviews were conducted with key informants, and participant observation was carried out before, during the intervention and afterwards in the communities. The interviews were recorded and transcribed, and analysed qualitatively for key themes, concepts and contradictions. RESULTS: Several barriers were identified that undermine the quality of child care practices, many linked to gender constructions and norms. The dominant concepts of masculinity created shame and embarrassment if men deviated from these norms, by cooking or caring for their children. The study provided evidence that participatory education supported new masculinities through public performances that encouraged men to take on these new roles. Invoking men's family responsibilities, encouraging new social norms alongside providing new information about different healthy recipes were all pathways by which men developed new 'emergent' masculinities in which they were more involved in cooking and child care. The transformational approach, intergenerational and intra-gendered events, a focus on agriculture and food security, alongside involving male leaders were some of the reasons that respondents named for changed gender norms. CONCLUSIONS: Participatory education that explicitly addresses hegemonic masculinities related to child nutrition, such as women's roles in child care, can begin to change dominant gender norms. Involving male leaders, participatory methods and integrating agriculture and food security concerns with nutrition appear to be key components in the context of agrarian communities.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.048
GPT teacher head0.309
Teacher spread0.261 · 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

Citations84
Published2016
Admission routes2
Has abstractyes

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