Os BRICS frente à pandemia da COVID-19: uma análise preliminar sobre políticas comparadas
Bibliographic record
Abstract
A pandemia do novo coronavírus (COVID-19) atingiu todos os países do mundo, impactando os sistemas de saúde e atingindo as economias, desde as bases produtivas nacionais até as cadeias de produção e comércio mundiais. Com isso, a pandemia vem reposicionando o papel das políticas públicas e dos Estados-nacionais, uma vez que capacidades estatais em saúde precisaram ser fortalecidas e programas econômicos e sociais precisaram ser desenvolvidos para resgatar empresas e empregos. O objetivo deste trabalho é verificar, de forma preliminar, como os países que compõem os BRICS, afora o Brasil, têm enfrentado a pandemia, apontando algumas tendências comuns em suas abordagens. Metodologicamente, buscamos identificar convergências e diferenças nas ações dos governos de cada país BRICS no que tange às medidas de contenção da doença, políticas relacionadas à economia e aos empregos, bem como iniciativas de cooperação internacional. Concluímos com possíveis lições que podem ser extraídas destas experiências para o Brasil.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".