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Record W4412844771 · doi:10.62049/jkncu.v5i2.296

Organizational Strategies for Addressing Barriers to Women’s Participation in Agricultural Cooperatives

2025· article· en· W4412844771 on OpenAlexfundno aff
M Bitange, Kennedy Munyua Waweru, Charles Wambu

Bibliographic record

VenueJournal of the Kenya National Commission for UNESCO · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCooperative Studies and Economics
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchInternational Development Research Centre
KeywordsBusinessAgriculturePublic relationsMarketingPolitical scienceGeography

Abstract

fetched live from OpenAlex

Most of the time, women's active participation is structural and stems from household and community sociocultural norms. Both the law and culture acknowledge males as the nominal owners of household assets in the vast majority of cases. Women consequently do not have equal access to money and benefits. Due to this lack of access, women's confidence is further undermined, which makes it rare for them to hold important positions in market-based agricultural and mixed cooperatives. The study adopted mixed method research design and targeted 45 registered dairy and coffee cooperative with a membership of 114,267 members in Kiambu County. Simple random sampling was used to sample 398 female members who participated in the study. Data was collected using questionnaires and key informant interview guides. Quantitative and qualitative data were collected. Quantitative data was analyzed using descriptive statistics while qualitative data was analyzed using content analysis. The findings indicated that Level of education and age have a significant influence on women participation with both variables having a p value of 0.000. The findings also indicate that organizational policy strategies significantly affect women participation in agricultural cooperatives at p=0.000 and r=0.33. The study recommends that agricultural cooperatives should institute policies that favor women participation such as coopting some women members.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.303
Teacher spread0.274 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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 venueJournal of the Kenya National Commission for UNESCOSame topicCooperative Studies and EconomicsFrench-language works237,207