MétaCan
Menu
Back to cohort
Record W4412808853 · doi:10.4314/rafea.v8i2.10

Impact of an improved cooking stove on the empowerment of women in rural areas in Southern Benin: case of the Guev Cooker

2025· article· en· W4412808853 on OpenAlexfundno aff
Victoire Modukpè K. C. Ogodja, Rose Fiamohe, Ambaliou O. Olounlade Ambaliou O. Olounlade, Charlemagne Igue Babatoundé, Jacob Afouda Yabi

Bibliographic record

VenueRevue Africaine d’Environnement et d’Agriculture · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsStoveCookerEmpowermentSocioeconomicsGeographyEconomic growthSociologyEconomicsArchaeology

Abstract

fetched live from OpenAlex

Description of the subject. Rural women use traditional cooking stove, which require them to spend a lot of time gathering wood and cooking. The use of these stoves reduces the possibility that women will be able to undertake an income-generating activity in order to be self-sufficient.Objective. This study aims to assess the impact of the use of the improved cooking stove "GUEV COOKER" on the empowerment of women in southern Benin.Methods. The study applies the experimental impact evaluation method known as randomized controlled trials and involved 531 women randomly assigned, with 266 beneficiary women and 265 non-beneficiary women in 5 municipalities in southern Benin, namely: Adjarra, Avrankou, Dangbo, Sakété, Ifangni. Given the small sample size, we conducted stratified random sampling based on three (3) variables for each group.Results. The results obtained show that the treated group (women who have benefited from the Guev Cooker improved cooking stove) and control group (women who have not benefited from the Guev Cooker improved cooking stove) were well balanced before the intervention. The use of the improved stove "GUEV COOKER" positively influenced the general empowerment score of women in the study area.Conclusion. The promotion of improved stoves that can be used by women in their households and in the various income-generating activities they undertake, as well as the promotion of women's employment in Benin, would facilitate their empowerment. Description du sujet. Les femmes rurales utilisent des foyers traditionnels qui leurs imposent de passer assez de temps aussi bien pour la collecte du bois que pour la cuisson. L’utilisation de ces foyers réduit la possibilité que les femmes peuvent avoir pour entreprendre une activité rémunérée afin d’être autonome. Objectif. Cette étude vise à évaluer l’impact de l’utilisation du foyer de cuisson amélioré « GUEV COOKER » sur l’autonomisation de la femme au sud Bénin.Méthodes. L’étude a utilisé la méthode expérimentale d’évaluation d’impact désignée comme les essais aléatoires contrôlés et a impliqué 531 femmes assignées de manière aléatoire avec 266 femmes bénéficiaires et 265 femmes non bénéficiaires dans 5 communes au sud du Bénin à savoir : Adjarra, Avrankou, Dangbo, Sakété, Ifangni. Compte tenu de la petitesse de la taille de l’échantillon, un échantillonnage aléatoire stratifié à partir de trois (3) variables pour chaque groupe a été utilisé.Résultats. Les résultats obtenus montrent que les groupes traités (les femmes qui ont bénéficié du foyer Guev Cooker) et contrôles (les femmes qui n’ont pas bénéficié du foyer Guev Cooker) étaient bien équilibrés avant l’intervention. L’utilisation du foyer amélioré « GUEV COOKER » a influencé positivement le score d’autonomisation générale des femmes de la zone d’étude.Conclusion. La promotion des foyers améliorés qui peuvent être utilisés par les femmes dans leurs ménages et dans les différentes activités génératrices de revenu qu’elles mènent et la promotion de l’emploi des femmes au Bénin faciliteraient leur autonomisation

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)0.001
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.241
Teacher spread0.232 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueRevue Africaine d’Environnement et d’AgricultureSame topicAgriculture and Rural Development ResearchFrench-language works237,207