A pandemia de Covid-19 e seus entrelaçamentos com desigualdade de gênero, insegurança alimentar e apoio social na América Latina
Bibliographic record
Abstract
Enquanto crises econômicas desencadeiam o aumento da insegurança alimentar (IA) e da desigualdade de gênero (DG), o apoio social tem mostrado aliviar esses impactos. No entanto, diferentemente de outros choques econômicos, a pandemia de Covid-19 incluiu no cenário de crise o isolamento social. Este estudo utilizou dados de pesquisa transversal coletados em 18 países da América Latina (AL) para avaliar as mudanças nas percepções de DG e sua associação com a IA e o apoio social durante período de crise econômica na região. Os resultados mostraram aumentos graduais nas percepções de DG na AL e que os entrevistados com IA e baixo apoio social eram os mais propensos a perceber a DG. Mulheres são mais vulneráveis à IA e à violência doméstica, e o isolamento social pode ser um agravante. Políticas públicas devem garantir que mulheres tenham maior controle sobre a renda e bens produtivos.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".