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Record W4308392466 · doi:10.3390/vaccines10111868

Using the Women Empowerment in Livestock Index (WELI) to Examine Linkages between Women Smallholder Livestock Farmers’ Empowerment and Access to Livestock Vaccines in Machakos County of Kenya: Insights and Critiques

2022· article· en· W4308392466 on OpenAlexfundno aff
Catherine Kaluwa, Jemimah Oduma, Faduma Abdullahi Abdirahman, Byalungwa Kyotos Kitoga, Angela Opondoh, John Muchibi, Brigitte Bagnol, Marieke Rosenbaum, Sylvia Onchaga, Meghan Stanley, Janetrix Hellen Amuguni

Bibliographic record

VenueVaccines · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsLivestockEmpowermentIndex (typography)Women's empowermentSocioeconomicsEconomic growthBusinessGeographyEconomicsForestry

Abstract

fetched live from OpenAlex

Livestock diseases are a major barrier to productivity for both male and female livestock keepers in Africa. In Kenya, two of the most devastating livestock diseases are Newcastle Disease (ND) in poultry and Contagious Caprine Pleuropneumonia (CCPP) in goats. Female livestock keepers tend to own more small ruminants (goats, sheep, etc.) and poultry and their livelihoods are adversely affected if their herds are not vaccinated against these diseases. Livestock farming has gender specific challenges and opportunities, with implications for the empowerment of women smallholder farmers, their household well-being, food security, and livelihoods. There is a need to estimate the level to which women benefit personally, socially, and economically from keeping livestock, yet there are very few studies that can measure if livestock production does in fact empower women smallholder livestock farmers. This study was done to examine linkages between women's empowerment and access and control over livestock products and vaccines. The Women Empowerment in Livestock Index (WELI) tool, which was customized to include questions on livestock vaccine access, was used to capture baseline data on empowerment scores for women in Machakos county, Kenya, prior to implementation of animal health and vaccine test models. In total, 400 participants were surveyed in two wards of Machakos County, Kola and Kalama, which were purposively selected. Women's empowerment was mapped to three domains (3DE): intrinsic agency (power within), instrumental agency (power to), and collective agency (power with) measured against adequacy in 13 indicators. Our results indicate that the household structure (female headed or dual headed household), age of respondents and number of members in a household influence the adequacy score. Work balance was the most significant negative contributor to women's disempowerment. Women contributed the most to livestock productive activities and attained adequacy in this area compared to men, directly impacting the WELI score. Women smallholder livestock farmers report low CCPP and ND vaccination rates, minimal knowledge on livestock diseases, a lack of access to cold chain storage and rarely visited veterinarians. The WELI score was 0.81 indicating a high level of empowerment for women in this community compared to men leading us to conclude that the overall WELI score was not an accurate indicator of women's empowerment in Machakos County. However, the decomposability of the index allows us to disaggregate the drivers of change and to examine how individual indicators contribute to disempowerment.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
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 head0.046
GPT teacher head0.284
Teacher spread0.237 · 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 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

Citations13
Published2022
Admission routes1
Has abstractyes

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