Maurice Tardif - trajectory of a researcher: between professionalization of education, critical thinking and contemporary risks
Bibliographic record
Abstract
Resumo Este texto apresenta a trajetória acadêmica do professor, intelectual e pesquisador Maurice Tardif, da Université de Montréal (Universidade de Montreal) no Canadá, por meio da realização de uma entrevista, realizada por Samuel de Souza Neto e Eliana Ayoub em maio de 2017. Maurice Tardif vem dedicando suas reflexões e pesquisas a temáticas educacionais relacionadas aos saberes docentes, à formação profissional, à divisão do trabalho na escola, bem como à inserção profissional e às profissões do ensino no contexto escolar. Ele discute a profissionalização do ensino, questionando o fato desse processo não emergir dos professores, mas de induções do estado ou de movimentos de valorização do magistério, desafiando os professores a lutarem pela sua própria identidade profissional. Além da criação de centros de pesquisa, como o Centre de Recherche Interuniversitaire sur la Formation et la Profession Enseignante (Crifpe – Centro de Pesquisa Interuniversitário sobre a Formação e a Profissão Docente), o que se observa é o nascimento de uma escola de pensamento, a Escola Quebequense sobre a Formação e a Profissão Docente.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".