Bibliographic record
Abstract
Au moment où, en France, la formation des enseignants suscite passions et inquiétudes et révèle les tensions qui traversent la société, ce numéro s’interroge sur la façon dont d’autres pays définissent les grandes options qui inspirent leurs dispositifs de formation et dont ils organisent la formation initiale et le développement professionnel des maîtres. Aucun modèle stabilisé ne semble émerger, même si la formation des enseignants, partout considérée comme un enjeu majeur, tend souvent à être allongée et fait l’objet de réformes. La confrontation des analyses permet cependant d’identifier des problématiques récurrentes : la question des savoirs et de la professionnalisation ; l’approche par compétences ; le rôle de l’État ; le choix des opérateurs ; la formation et le recrutement. As France sets out to thoroughly remodel its teacher training system, this issue of the Revue internationale d’éducation de Sèvres examines other national traditions and approaches: Quebec, England, Argentina, the USA, France, Sweden, Grece, countries of the Western Balkans and South Korea. No stabilised model appears to be emerging, although teacher training, which is everywhere considered a major stake, often tends to be lengthened and to undergo reforms. Recurrent issues can be identified through the analyses offered here: the balance between knowledge and professionalisation; competence-based approaches; the role of the State; the choice of institutions; training and recruitment. En estos momentos en que Francia emprende una reforma profunda de su sistema de formación de docentes, este número de la Revue internationale d’éducation de Sèvres presenta un estudio del modo en que países con tan diferentes tradiciones como Quebec, Inglaterra, Argentina, Estados Unidos, Francia, Suecia, Grecia, países de los Balcanes Occidentales y Corea del Sur se organizan para atender dicha profesionalización. De momento, ningún patrón estabilizado se destaca, a pesar de que la formación de docentes, considerada en todas partes como un reto mayor, a menudo se beneficia de una extensión y entra en proceso de reforma. Un análisis comparativo permite identificar problemáticas recurrentes: la cuestión de los saberes y de la profesionalización; el enfoque de competencias; el papel del Estado; la elección de los operadores; la capacitación y la contratación.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.098 | 0.030 |
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".