Qualitative exploration of the dynamics of women’s dietary diversity. How much does economic empowerment matter?
Bibliographic record
Abstract
OBJECTIVE: This study qualitatively examined dietary diversity among married women of reproductive age who engaged in two socio-economic activities to explore the dynamics of food availability, access, costs and consumption. DESIGN: Qualitative in-depth interviews. The food groups in the Minimum Dietary Diversity for women were used to explore women's dietary diversity. IDI were used to develop a roster of daily food consumption over a week. We explored food items that were considered expensive and frequency of consumption, food items that women require permission to consume and frequency of permission sought and the role of economic empowerment. Data analysis followed an inductive-deductive approach to thematic analysis. SETTING: Rural and peri-urban setting in Enugu State, Nigeria. PARTICIPANTS: Thirty-eight married women of reproductive age across two socio-economic groupings (women who work only at home and those who worked outside their homes) were recruited in April 2019. RESULTS: Economic empowerment improved women's autonomy in food purchase and consumption. However, limited income restricted women from full autonomy in consumption decisions and access. Consumption of non-staple food items, especially flesh proteins, would benefit from women's economic empowerment, whereas staple food items would not benefit so much. Dietary diversity is influenced by food production and purchase where factors including seasonal variation in food availability, prices, contextual factors that influence women's autonomy and income are important determinants. CONCLUSION: With limited income, agency and access to household financial resources coupled with norms that restrict women's income earning, women continue to be at risk for not achieving adequate dietary diversity.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".