Travailler en interprofessionnalité en contexte de clinique universitaire : l’exemple de la formation initiale en orthopédagogie et en travail social
Bibliographic record
Abstract
Les cliniques universitaires d’orthopédagogie et de travail social de l’UQAC ont été l’hôte d’un projet visant, grâce à la mise en place de dispositifs de collaboration, le développement de compétences interprofessionnelles. L’article a pour but de décrire la compréhension du travail en collaboration interprofessionnelle des 25 étudiantes participantes en présentant leurs connaissances avant le projet et leurs impressions après le projet. L’analyse qualitative de leur discours, issu d’entrevues semi-dirigées, a fait ressortir un changement dans la vision initiale du travail en interprofessionnalité, et ce, en lien aux dispositifs de collaboration, au contexte réel de pratique et à l’encadrement professoral.
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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 | 0.023 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.017 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.006 |
| 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".