What empowerment indicators are important for food consumption for women? Evidence from 5 sub-Sahara African countries
Bibliographic record
Abstract
This paper draws on data from five sub-Sahara African countries; Uganda, Rwanda, Malawi, Zambia, and Mozambique consisting of 10,041 married women who were cohabitating with a male spouse. The study aim was to investigate the relationship between women's empowerment and women's dietary diversity and consumption of different food items. Women's empowerment was measured using the indicators in the five domains of Women's Empowerment in Agriculture index (WEAI) and women's dietary diversity and food consumption was examined using the women's dietary diversity score (WDDS) measure. OLS and LPM regressions were used and analyses were confirmed using marginal effects from Poisson and logistic regressions. Results suggest that three out of the 10 WEAI indicators of empowerment showed different magnitude and direction in significant associations with improved WDDS and varied associations were found in three out of the five countries examined. In addition, the three significant empowerment indicators were associated with the consumption of different food groups in three out of the five countries examined suggesting that diverse food groups account for the association between the WEAI and WDDS. Improved autonomy, and input in production were associated with improved likelihoods of consumption of dairy products, and fruits and vegetables including vitamin A-rich produce. Empowerment in public speaking was associated with improved consumption of other fruits and vegetables including vitamin A-rich produce. The varied nature of empowerment indicators towards improving women's dietary diversity and food consumption suggests that different empowerment strategies might confer different benefits towards the consumption of different food groups. Further, findings imply that interventions that seek to empower women should tailor their strategies on existing contextual factors that impact on women.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".