Des stages en français pour se préparer à travailler auprès des communautés francophones en situation minoritaire
Bibliographic record
Abstract
Dans l’objectif d’augmenter le nombre de professionnelles et professionnels pouvant offrir des services sociaux et de santé en français dans les communautés francophones en situation minoritaire (CFSM), des stages en français ont été offerts à des étudiantes et étudiants bilingues de programmes de formation professionnelle offerts en anglais au sein d’universités canadiennes. L’expérience a été positive pour l’ensemble des parties prenantes : stagiaires, éducatrices-cliniciennes et responsables de la formation clinique. Après cette expérience, les stagiaires ont mentionné avoir une meilleure connaissance des défis d’accès aux services rencontrés par les CFSM et se sentir plus en mesure d’offrir des services en français à ces communautés.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".