Eficácia dos processos de linkagem na avaliação educacional em larga escala
Bibliographic record
Abstract
Em 1997, por meio do Sistema Nacional de Avaliação da Educação Básica (Saeb), definiu-se a escala de proficiência para o Brasil. A partir de então, praticamente todas as avaliações em larga escala realizadas têm procurado manter uma comparabilidade de resultados com essa escala, por intermédio da Metodologia da Teoria da Resposta ao Item (TRI). Entretanto, observa-se uma diversidade de situações ao se analisar as diferentes avaliações realizadas pelos Estados brasileiros e até no próprio Saeb. Neste artigo, apresentaremos alguns aspectos técnicos necessários para garantir a comparabilidade nos procedimentos de linkagem de avaliações, bem como as características das avaliações do Saeb e de alguns Estados brasileiros ao longo do tempo.
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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 | 0.108 | 0.319 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".