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Record W4405256014 · doi:10.1080/00083968.2024.2427840

From negotiated to covert: married women’s agency in staple crop value chains in Kenya, Ghana, South Africa and Uganda

2024· article· en· W4405256014 on OpenAlexafffundvenue
Lincoln Addison, Christopher Gore, Sylvia Bawa, Matthew A. Schnurr

Bibliographic record

VenueCanadian Journal of African Studies / Revue canadienne des études africaines · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsDalhousie UniversityYork UniversityToronto Metropolitan UniversityMemorial University of Newfoundland
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAgency (philosophy)Economic growthSocioeconomicsFocus groupEmpowermentDeveloping countryPolitical scienceGeographySociologyBusinessEconomicsMarketingSocial science

Abstract

fetched live from OpenAlex

This article examines married women’s agency in marketing and income use for staple crops grown on jointly held fields in four African countries: cowpea in Ghana, maize in South Africa and Kenya, and matooke banana in Uganda. The article is based on a series of workshops in each country in which small-scale farmers participated in focus group discussions and a participatory mapping of value chains. Our results show that in Ghana and South Africa, wives exercise agency through acknowledging and appealing to their husbands’ authority, using their roles as custodians of income to shape expenditure, and relying on non-confrontational persuasion. In Kenya and Uganda, women withdraw their labour, hide crops, and redirect their energy to marketing crops grown on separate fields. These findings demonstrate the multiple and complex ways married women exercise agency in the domains of marketing and income use.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.034
GPT teacher head0.221
Teacher spread0.187 · 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 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

Citations0
Published2024
Admission routes3
Has abstractyes

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