Gender disparities in rural livelihood diversification and household food insecurity in northern Ghana
Why this work is in the frame
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Bibliographic record
Abstract
Although income diversification is a well-established strategy for mitigating poverty and household food insecurity, gendered dimensions have been under-investigated. Examining a specific district in northern Ghana with heightened levels of food insecurity, we asked two questions: 1) Does income diversification reduce the risk of experiencing household food insecurity? and if so, 2) Does the relationship differ between women and men? This investigation used univariate, bivariate, and multivariate analysis of a cross-sectional survey of married spouses in 435 households. Results indicate that income diversification is linked with greater reporting of household food insecurity (OR = 1.23, p < 0.01). The link between livelihood diversification and household food insecurity is stronger among women than their husbands (OR = 1.27, p < 0.01). While we do not know whether diversified livelihoods cause food insecurity or food insecurity causes someone to diversify their income, improving the stability of income sources for both women and men in ways that consider gendered food dynamics is needed, particularly in rural African geographies disproportionally dependent upon biophysical environments and economies that are rapidly changing. African geographers and rural development professionals need to consider multiple individual and diverse gendered experiences for progressing scholarship that strives to explain and resolve uneven livelihood outcomes for household food security.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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