Brazilian Families Facing the COVID-19 Outbreak
Bibliographic record
Abstract
In this paper, we discuss the impact of COVID-19 on Brazilian families, considering socioeconomic data from before and during the outbreak. The coronavirus threatens Brazil’s entire population. Since May 2020, Brazil is considered the pandemic epicenter, presenting high rates of infections and deaths at least up to the end of August 2020. Families in which members may have lost their jobs or are living from informal work face the challenge of protecting themselves from COVID-19, but also of maintaining financial conditions despite the risk. Access to healthcare has proven to be more precarious for the poor, Indigenous, Black, street population, women, and LGBTQI+. Impacts on the mental health of family members who comply with social isolation and are overburdened with domestic duties, home office and their children’s education by digital media are increased by stress, anxiety, and uncertainties about the future. Due to the great impact COVID-19 has provoked on Brazilian families, already existing socioeconomic iniquities increased during the pandemic. Unemployment, bad basic sanitation conditions and a high rate of informal work contrast with the situation of high-income families. The post-pandemic period will be decisive for Brazil to prioritize the recovery of its already existing public policies. We suggest the proposed initiatives be organized around the goal of mitigating adverse effects on mental health aggravated by COVID-19.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".