TECENDO REFLEXÕES: SOBRE A OBRA A MULHER QUE MATOU OS PEIXES DE CLARICE LISPECTOR
Bibliographic record
Abstract
O presente artigo propõe uma análise crítica da obra A mulher que matou os peixes (1968), de Clarice Lispector, adentrando o universo da literatura infantil. Abordaremos aspectos empregados na narrativa como o diálogo com o leitor, o uso da oralidade, o emprego de ilustrações e a presença da temática da morte. Para embasar nossa análise, utilizaremos como referencial teórico os escritos de Coelho (2000), Zilberman (2015) e Lajolo (1988) sobre literatura infantil, além das reflexões de Zinani (2010), Moisés (1970) e Serra (1998) acerca das características presentes na obra de Clarice Lispector. A escolha por explorar o livro em questão foi motivada pela maneira como a autora aborda os dilemas da vida, tornando-os acessíveis e compreensíveis para os leitores infantis. Suas histórias cotidianas permitem que os jovens leitores se identifiquem e compreendam melhor suas próprias experiências.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".