Bibliographic record
Abstract
Les transitions scolaires sont des moments clés pour les élèves, mais aussi pour les professionnels de l’éducation qui doivent les accompagner dans ce processus et les aider à mobiliser leurs ressources. De l’entrée dans la scolarité jusqu’aux formations postobligatoires, comme lors du passage entre le primaire et le secondaire, les enseignants et les spécialistes jouent un rôle essentiel auprès des jeunes et doivent exercer une attention vigilante. Les auteurs de ce livre suscitent la réflexion et proposent des pistes d’action afin de faciliter les nombreuses transitions qu’auront à vivre les élèves tout au long de leur parcours de formation. Les points de vue multiples et complémentaires qu’apportent les contributions d’auteurs issus des sciences de l’éducation, de la psychologie, de la sociologie et de l’orientation professionnelle et qui proviennent du Québec, de la Suisse, de la France et de l’Angleterre brossent un tableau aussi complet que possible des enjeux, des risques et des ressources liés aux transitions scolaires. Cet ouvrage aidera tout professionnel œuvrant dans le milieu scolaire à optimiser son rôle auprès des jeunes.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.005 |
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".