The Household Food Security Implications of Disrupted Access to Basic Services in Five Cities in the Global South
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
COVID-19 has caused significant disruptions regarding the extent to which households can access basic services and resources in cities around the world. Previous studies have indicated a predictive relationship between the consistency of resource access and food access among urban households. These investigations, however, have predominantly been isolated to Southern Africa and have not accounted for other dimensions of food security. To test whether these results are observable outside Southern Africa, and with a more multidimensional measure of food security, this investigation proposes a method for building an index of urban household food access, utilization and stability. The scores for the constructed index are then compared across household survey samples collected from five cities in the Global South. The investigation then assesses the predictive relationship between the consistency of household resource access and this more multidimensional index of food insecurity. While the general trend of inconsistent resource access predicting food insecurity is confirmed, there are geographic differences in the strength and quality of this relationship. These findings suggest that the resource access disruptions inflicted by COVID-19 will likely have a heterogeneous impact on urban food security dependent upon the affected resource and the city in which a given household resides.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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