Family Structure and Severe Food Insecurity in Maputo and Matola, Mozambique
Bibliographic record
Abstract
The rapid growth of Maputo and Matola (neighbouring cities in Mozambique) has dramatically shifted the vulnerability profiles of these cities. Poor neighbourhoods across these two cities may now face the prospect of becoming food deserts. Scholars have defined African urban food deserts by the co-occurrence of poverty and food insecurity. This study aims to assess the assumed relationship between resource poverty and food insecurity in the African urban food desert concept and to assess the contribution of household demographics to this relationship. Using household survey data collected in 2014 across Maputo and Matola, this investigation demonstrated that inconsistent access to water, electricity, medical care, cooking fuel, and cash was associated with increased odds of severe household food insecurity across both cities. In addition, a nuclear household family structure was associated with reduced odds of severe food insecurity in both cities (even when taking limited resource access into account). These findings suggest that the severe food insecurity vulnerabilities associated with African urban food deserts may differ according to the family structure of households in Maputo and Matola.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".