MétaCan
Menu
Back to cohort
Record W4402151701 · doi:10.32920/ihtp.v4i2.2070

Examining the relationship between women’s empowerment and food security in low- and middle-income countries: A narrative review

2024· review· en· W4402151701 on OpenAlexvenueno aff
Farzaneh Barak, Hugo Melgar‐Quiñonez

Bibliographic record

VenueInternational Health Trends and Perspectives · 2024
Typereview
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
Fundersnot available
KeywordsEmpowermentFood securityOperationalizationContext (archaeology)AgricultureEconomic growthScopusPolitical scienceInclusion (mineral)Women's empowermentPsychological interventionBusinessSociologyEconomicsPsychologyGeographySocial scienceMEDLINE

Abstract

fetched live from OpenAlex

Prior research has proposed women’s empowerment in agriculture as one of the strategies to mitigate household and individual food insecurity within nutrition-sensitive agriculture interventions. Yet the current evidence on this relationship is inconclusive requiring further exploration to elucidate the pathways through which women’s empowerment is associated with food security. This literature review aimed to draw insights from studies on women’s empowerment and food security and identify the related challenges and best practices in this pathway within the context of low- and middle-income countries. Scopus, PubMed, and Global Health databases were searched, as well as reference lists for articles. In total 21 articles met the inclusion criteria. Findings suggest a mixed relationship between women’s empowerment and food security and highlighted a gap in conceptualizing and operationalizing food security. To achieve sustainable food security, particularly in the aftermath of COVID-19, researchers and stakeholders must respond to the broader context of gender systems that restricts women’s rights and access to productive resources to achieve food security.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.570
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.308
GPT teacher head0.513
Teacher spread0.205 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternational Health Trends and PerspectivesSame topicFood Security and Health in Diverse PopulationsFrench-language works237,207