Urban food insecurity and its determinants: a baseline study of Bengaluru
Why this work is in the frame
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Bibliographic record
Abstract
There is an increasing need to study urban food security in the global South. This is because of the monetization of food in urban areas and compounding vulnerability from other deprivations such as lack of access to infrastructure. We assess these claims in this paper, based on a city-wide household survey in Bengaluru (Bangalore) carried out in 2016 that used experiential measures of food security like the Household Food Insecurity Access Scale. We find that income and consumption do not have a clear relationship with food insecurity. However, socioeconomic dimensions like education level and wage type of the household head, and infrastructural dimensions like housing typology, and water connection are strongly related to food security. Through this work, we attempt to establish the baseline evidence on the current status of food security in Bengaluru, to lay the foundation for a future research agenda on urban food security in India.
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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 | 0.000 |
| 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 it