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Record W7034749216

Women, livestock ownership and markets: Bridging the gender gap in eastern and southern Africa

2013· article· en· W7034749216 on OpenAlexfundno aff

Bibliographic record

VenueCGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Studies and Ethnography
Canadian institutionsnot available
FundersInternational Fund for Agricultural DevelopmentInternational Livestock Research InstituteInstituto de Investigação Agrária de MoçambiqueDepartment for International DevelopmentUniversity of PretoriaInternational Labour OrganizationUnited States Agency for International DevelopmentInternational Development Research CentreInternational Fine Particle Research InstituteUnited Nations Development Programme
KeywordsLivestockFood securityPovertyAsset (computer security)TanzaniaPastoralismMarket accessProduct (mathematics)Production (economics)
DOInot available

Abstract

fetched live from OpenAlex

This book provides empirical evidence from Kenya, Tanzania and Mozambique and from different production systems of the importance of livestock as an asset to women and their participation in livestock and livestock product markets. It explores the issues of intra-household income management and economic benefits of livestock markets to women, focusing on how types of markets, the types of products and women’s participation in markets influence their access to livestock income. The book further analyses the role of livestock ownership, especially women’s ownership of livestock, in influencing household food security though increasing household dietary diversity and food adequacy. Additional issues addressed include access to resources, information and financial services to enable women more effectively to participate in livestock production and marketing, and some of the factors that influence this access. Practical strategies for increasing women’s market participation and access to information and services are discussed. The book ends with recommendations on how to mainstream gender in livestock research and development if livestock are to serve as a pathway out of poverty for the poor and especially for women.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.104
GPT teacher head0.348
Teacher spread0.244 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations8
Published2013
Admission routes1
Has abstractyes

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