Gendered Mobilities, Food Access, and Rural-Urban Linkages in Blantyre, Malawi
Bibliographic record
Abstract
People in African cities access food from a variety of sources, including but not limited to: supermarkets; traditional marketplaces; informal vendors; urban and rural farms, and rural markets. Optimising the quality, price, and variety of foods requires mobility, which is often constrained by gender roles. This paper draws on participative mapping and in-depth interviews conducted in Blantyre, Malawi, a city in which robust urban-rural linkages have economic, political, and social dimensions that fundamentally shape urban household food security. The ability to frequently visit rural and peri-urban places to grow and buy food can mitigate the effect of inadequate and precarious urban incomes on household food security. The paper argues that gendered mobility constraints can impact the food security of entire households by hindering food access. The focus on urban residents moving between rural and urban spaces for their livelihoods highlights the centrality of urban-rural linkages for urban livelihoods. While existing urban food security research has focused on urban-rural linkages in terms of human migration and food supply chains, the gendered focus of this case study shows a consistent and vital stream of people and food crossing the urban/rural boundary and calls for new perspectives on spatial categories of analysis.
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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 | 0.001 | 0.001 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| 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".