Conception d’outils de mesure de l’offre active de services sociaux et de santé en français en contexte minoritaire
Bibliographic record
Abstract
Dans les communautés francophones en situation minoritaire, le besoin d’une offre active des services en français, plutôt que d’un service qui suit la demande, est de plus en plus reconnu. Les professionnels en santé et en service social doivent être formés à cette approche et les résultats devront être évalués. Cet article décrit le processus de création et de validation de contenu (recension d’écrits, consultations d’experts, sondage Delphi pancanadien) de deux questionnaires portant sur les comportements caractéristiques de l’offre active de services sociaux et de santé en français : le premier mesurant les comportements individuels d’offre active des intervenants et le deuxième mesurant la perception de ces derniers du soutien organisationnel à l’offre active.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".