William Pinar Entrevista
Bibliographic record
Abstract
Esta entrevista segue um formato diferenciado, com um unico entrevistador que dirige suas questoes a seis pesquisadores do campo do curriculo no Brasil. Trata-se da primeira atividade1 realizada no âmbito do projeto ―Internacionalizacao dos Estudos Curriculares‖, coordenado pelo Dr.William Pinar, da University of Brisitish Columbia, financiado pelo Social Sciences and Humanities Research Council of Canada. O objetivo maior da pesquisa era entender como a ―internacionalizacao‖ — definida especificamente como ―conversa complicada‖ com colegas em contextos diferentes dos nossos — pode (ou nao) contribuir para o desenvolvimento intelectual do campo do curriculo de formas nacionalmente distintas. Seus resultados estao sendo veiculados no livro ―Curriculum Studies in Brazil‖, editado por William Pinar e publicado pela Editora Palgrave. Com a palavra, o entrevistador William Pinar e os entrevistados, pesquisadores que aceitaram participar do referido projeto: Alice Casimiro Lopes (UERJ), Antonio Carlos Amorim (UNICAMP), Elizabeth Macedo (UERJ), Ines Barbosa de Oliveira (UERJ) e Nilda Alves (UERJ).
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.044 | 0.014 |
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".