Efeitos de Tamanho da Sala no Desempenho dos Alunos: Evidências Usando Regressões Descontínuas no Brasil
Bibliographic record
Abstract
Resumo Este estudo utiliza a metodologia de regressão descontínua fuzzy, considerando o tamanho da sala predito pela função de Maimonides (Angrist & Lavy, 1999) como instrumento para o tamanho da sala observado, para avaliar o impacto de políticas públicas que estipulem um número máximo de alunos por turma no Brasil. Em particular, foram analisados os efeitos de resoluções e portarias municipal e estadual de São Paulo, Minas Gerais e Santa Catarina sobre as notas de alunos do 5º e 9º ano na Prova Brasil 2015. Os resultados mostram que não existam evidências estatisticamente significantes de que o tamanho da sala tenha impacto nas notas dos alunos. As análises de robustez performadas também concluem não haver efeito.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.040 |
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".