Inadimplência nos serviços de água e esgotamento sanitário em Manaus/AM: uma análise dos impactos da pandemia
Bibliographic record
Abstract
O desemprego, a queda na renda e a alta da inflação no Brasil no período pandêmico afetaram as famílias e seus níveis de endividamento, comprometendo sua capacidade de pagamento, inclusive, de serviços básicos como energia elétrica, água e esgotamento sanitário. Este trabalho objetivou, de forma geral, analisar o endividamento dos clientes dos serviços de água e esgotamento sanitário do município de Manaus/AM, antes e após a pandemia do Covid-19. Trata-se de pesquisa quantitativa e qualitativa descritiva, tendo se utilizado de informações da prestadora dos serviços no município. Observou-se que houve um aumento significativo do endividamento dos clientes após o início da pandemia, com destaque para as economias comerciais e residenciais, a situação geral foi de piora no quadro de endividamento, tanto em termos de novos devedores quanto em termos de valores devidos, cabendo ao poder público a tomada das medidas cabíveis.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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; both teacher heads agree on what is shown here.
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".