O ENSINO EXPLÍCITO: UM MEIO PARA TORNAR EFICAZ NOSSO SABER PEDAGÓGICO – ENTREVISTA COM CLERMONT GAUTHIER
Bibliographic record
Abstract
Clermont Gauthier e Professor Titular do Departamento de Estudos sobre o Ensino e a Aprendizagem na Faculdade de Ciencias da Educacao na Universidade Laval desde 1989. E titular da Cadeira de Pesquisa do Canada em estudos para a Formacao de Professores da Universidade Laval (Quebec) e membro fundador do Centro de Pesquisa Interuniversitaria para a Formacao e a Profissao Docente (CRIFPE). Ao longo de sua carreira universitaria publicou, como autor ou em colaboracao, mais de 40 livros e mais de uma centena de artigos e capitulos de livros sobre os temas pedagogia – suas origens e fundamentos – correntes pedagogicas, praticas pedagogicas eficazes e formacao de professores. A entrevista foi realizada em 18 de dezembro de 2012, ocasiao em que a entrevistadora realizava seu Doutorado Sanduiche na Universidade Laval de Quebec sob orientacao de Clermont Gauthier. As entrevistadoras acrescentaram notas explicativas, com o intuito de facilitar a compreensao de alguns aspectos.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".