Bibliographic record
Abstract
Nous proposons dans ce texte une réflexion et une discussion sur la formation mathématique des futurs enseignants au secondaire. Cette préparation mathématique semble souvent considérée comme un allant de soi. Celle-ci nous apparaît toutefois centrale à re-penser à la lumière des travaux de recherche récents dans le domaine : À quelles expériences et pratiques mathématiques devraient être confrontés les futurs enseignants du secondaire pour pouvoir enseigner les mathématiques ? La tentative de réponse que nous apportons à cette question est basée sur une analyse des travaux de recherche portant sur la formation des enseignants en mathématiques en regard de ses incidences possibles sur la pratique des futurs enseignants, ainsi que sur les recherches portant sur les connaissances mathématiques des enseignants. Ces travaux viennent fortement questionner la nature des expériences et pratiques mathématiques auxquelles ces enseignants sont habituellement confrontés dans leur formation
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".