S’Orienter : un programme pour transformer les représentations sexospécifiques d’élèves sur les métiers et les professions
Bibliographic record
Abstract
Cet article porte sur l’implantation et les retombées du programme de groupe S’Orienter, visant à transformer les représentations sexospécifiques d’élèves du secondaire sur les métiers et les professions, représentations qui, en limitant les aspirations professionnelles, peuvent influencer l’orientation scolaire et professionnelle. Les analyses, menées dans une perspective culturelle historique de l’activité, ont permis de dégager que la participation au programme S’Orienter – notamment par les débats introduits autour de représentations sexospécifiques – soutient chez les élèves le développement d’un rapport plus conscient à ces représentations et à la façon dont elles peuvent affecter leurs choix éducatifs et professionnels.
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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 | 0.004 | 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 | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".