Food security status in times of financial and political crisis in Brazil
Why this work is in the frame
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Bibliographic record
Abstract
This study sought to describe the changes in the food security status in Brazil before and during its most recent financial and political crisis, as well as to explore associations between food security and socioeconomic factors during the crisis. This cross-sectional study analyzed data from two different sources: the Brazilian National Household Sample Survey for 2004 (n = 112,479), 2009 (n = 120,910), and 2013 (n = 116,192); and the Gallup World Poll for 2015 (n = 1,004), 2016 (n = 1,002), and 2017 (n = 1,001). Household food security status was measured by a shorter version of the Brazilian Food Insecurity Scale, consisting of the first 8 questions of the original 14-item scale. Descriptive and logistic regression analyses were performed to assess the changes in food security and their association with socioeconomic factors. Results suggest that during the crisis the percentage of households classified as food secure declined by one third (76% in 2013 to 49% in 2017) while severe food insecurity tripled (4% in 2013 to 12% in 2017). Whereas before the crisis (2013) 44% of the poorest households were food secure, by 2017 this decreased to 26%. Household income per capita was strongly associated with food security, increasing by six times the chances of being food insecure among the poorest strata. Those who reported a low job climate, social support or level of education were twice as likely to be food insecure. Despite significant improvements between 2004 and 2013, findings indicate that during the crisis Brazil suffered from a great deterioration of food security, highlighting the need for emergency policies to protect and guarantee access to food for the most vulnerable.
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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 | 0.001 |
| 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 | 0.001 |
| 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 it