Examen de portée sur les pratiques de mentorat virtuel de soutien à l’orientation d’élèves et d’étudiant·es
Bibliographic record
Abstract
Le mentorat virtuel gagne en popularité dans le champ de l’éducation en raison de sa souplesse et de son accessibilité. Or, l’apport de ces nouvelles pratiques ainsi que les défis qu’elles posent, en contexte d’orientation, demeurent méconnus. Cet examen de portée (scoping review) propose un état de connaissances sur les pratiques de mentorat virtuel de soutien à l’orientation chez les personnes adolescentes et les jeunes adultes de niveau secondaire, collégial ou universitaire. Un total de 18 articles empiriques, révisés par les pairs, publiés du 1er janvier 2016 au 1er juin 2022, ont fait l’objet de synthèses et d’analyses. Les résultats montrent des apports sur le plan du processus de prise de décision de carrière et de la consolidation du choix professionnel, selon certaines modalités et conditions favorables pour les mentor·es et mentoré·es. Les recherches sur le mentorat virtuel demeurent cependant limitées à des populations particulièrement minoritaires et vulnérables.
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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 | 0.025 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".