Deconstructing leisure time and workload: case of women bean producers in Kenya
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background The notion of leisure became pronounced more than 20 years ago when women who worked on or out of the farm came home to a “second shift,” which entailed domestic work and childcare. This gap continues today not only between men and women but also among women and men. Women's challenges in terms of their leisure arise out of or are shaped by social norms and different life contexts. Method The Women's Empowerment in Agriculture Index (WEAI) was conducted to understand women's empowerment and disempowerment status in agricultural activities in five counties in Kenya in 2017. In 2019, focus group discussions were carried out in two of the five counties to understand how men and women farmers define leisure and assess the leisure gap and its effect on women's farm and household activities. We were also interested in understanding how men's and women's workload affects leisure and other productive economic activities, resulting in empowerment and how women’s unpaid work contributes to income poverty. Result The WEAI showed that 28% of disempowerment (5DE) in women farmers is due to lack of time for leisure activities and 18% from being overworked. This means that the time indicator accounts for 46% of disempowerment in Kenyan women bean farmers. Men in Bomet and Narok spent more time than women in raising large livestock and leisure. Women in Bomet spent more time than men in cooking and domestic work (fetching water and collecting fuelwood), while men in Bomet spent more time than women in managing their businesses. Conclusion Work overload is a constraining factor to women's empowerment in bean production and agricultural productivity. What is considered leisure for men and women is embedded in society’s social fabrics, and it is contextual. This paper highlights instances where leisure provides a way for women to embody and/or resist the discourses of gender roles in the bean value chain and households to enhance food security and health.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it