VIAGENS NA MINHA TERRA E PETER PAN: A AUTOTEORIZAÇÃO LITERÁRIA E SUAS RELAÇÕES COM O ENSINO
Bibliographic record
Abstract
Partindo do pressuposto de que o principal conflito no ensino de Literatura no Ensino Médio é o grande enfoque na história da literatura, viu-se a necessidade de pensar o texto literário como protagonista. Entende-se que a abordagem exclusiva da história da literatura diminui a aparição do texto literário nas aulas, o que faz com que os alunos não tenham contato com o objeto de estudo da disciplina de Literatura, a obra literária. Com o intuito de colocar teoria e literatura lado a lado, optou-se por articular o mecanismo de autoteorização. Esse mecanismo visa abordar a teoria a partir das próprias obras literárias. Para explorá-lo foram selecionadas as obras Viagens na minha terra, de Almeida Garrett, e Peter Pan, de James Barrie. Como resultado das reflexões, será discutido de que forma a autoteorização literária contribui com o ensino de literatura no Ensino Médio. Serão utilizados: Culler; Volobuef; Jouve; e as OCEM.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".