Avaliação de Juízes: Um Modelo Estatístico para Perfilação de Avaliadores
Bibliographic record
Abstract
Neste artigo apresentamos um modelo para monitoramento de professores na avaliação de redações de acordo com as competências da redação do ENEM/INEP. Nosso modelo quantifica a confiabilidade e a concordância entre juízes baseado no coeficiente de correlação de Pearson aplicado às notas gerais, e também sobre as competências da grade de correção. Como resultado da aplicação do modelo observou-se a divergência entre dois professores na Competência 3, com um fator de correlação de ρ = -0.58. Ainda, alguns avaliadores obtiveram uma alta concordância com ρ = 1, demonstrando um alinhamento na forma de avaliar a Competência 2. As competências que denotam frequentemente uma discrepância acentuada são um sinal da necessidade de treinamento para o alinhamento dos avaliadores.
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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 | 0.016 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".