Uncovering the Intersections of Women’s Empowerment and Gender Equality in Climate Adaptive Capacities in Climate Hotspots for Women in Zambia
Bibliographic record
Abstract
Climate change risks exacerbating gender inequalities in agrifood systems; hence, the importance of understanding how women’s empowerment and gender equality of climate adaptive capacities relate. Using primary gender-disaggregated intrahousehold data collected in climate hotspots in Zambia, this study shows a positive relationship between women’s empowerment in the household and intrahousehold gender equality in access, knowledge and adoption of climate-smart agricultural practices. Showing that different dimensions of women’s empowerment – gender norms, access to resources and group membership – relate differently with gender-equal adaptive capacities, the study emphasizes the importance of a contextual analysis, unpacking the prevailing key constraints to gender equality, and the need for simultaneous investments in women’s empowerment and gender-equitable access to climate information services and climate-adaptive practices.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".