Les conditions d’insertion professionnelle des enseignants de l’Abitibi-Témiscamingue et du Nord-du-Québec et les mesures de soutien dont ils bénéficient en début de carrière
Bibliographic record
Abstract
-Tmiscamingue et du Nord-du-Qubec et les mesures de soutien dont ils bnficient en dbut de carrire Formation et profession 31(2) 2023 1 sum Cet article vise comprendre les conditions d'insertion professionnelle des enseignants dbutants en Abitibi-Tmiscamingue et au Nord-du-Qubec et les mesures de soutien dont ils bnficient en dbut de carrire. Les rsultats d'une recherche mixte combinant une enqute par questionnaire et des entrevues semi-structures menes auprs de 14 enseignants et cinq exenseignants montrent que les novices s'insrent dans des conditions difficiles souvent sans soutien ni accompagnement structur. Beaucoup remettent en question leur choix de carrire et pensent souvent quitter la profession. Il en ressort qu'une meilleure insertion des novices ncessite la mise en place de dispositifs de soutien l'insertion fonds sur leurs besoins.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".