Implicações da pandemia COVID-19 para a segurança alimentar e nutricional no Brasil
Bibliographic record
Abstract
The emergence of COVID-19 in Brazil further explained the massive discrepancy between different social realities coexisting in the country, rekindling the discussions about food and nutrition security, similarly to what has been happening in other countries facing the same pandemic situation. In this paper, we argue that the risks to hunger and food security in Brazil have been present since 2016 and are now being exacerbated due to the emergence of the COVID-19 epidemic. This situation requires knowing the extent and magnitude of the issue and articulation of measures in the three governmental spheres(federal, municipal and state) to ensure access to adequate and healthy food and reduce the disease's adverse effectson the diet, health, and nutrition among the most vulnerable people. Thus, this work aims to contribute to the debate on the measures to be adopted by governments and society to promote and ensure food and nutrition security and prevent insecurity and the expansion of hunger during and after the social and health crisis created by the pandemic.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".