Increasing the English-Language Content on Francophone Minority School Boards' Websites in Canada
Bibliographic record
Abstract
Ce texte présente les résultats d’une étude longitudinale portant sur le contenu anglais des sites Web des conseils scolaires de langue française en milieux minoritaires partout au Canada, reconnaissant l’évolution du profil langagier de la situation familiale des conseils. Une approche de recherche documentaire a été utilisée pour analyser l’évolution du contenu destiné à un public non francophone, permettant à ce public d’avoir accès à de nouvelles informations pertinentes en anglais. Il a été observé que la majorité des conseils scolaires de l’Ouest canadien et de l’Ontario ont accru la présence de l’anglais sur leurs sites Web. Le Canada atlantique (à l'exception du Nouveau-Brunswick) a suivi cette tendance. Il est à noter que d'autres langues et contenus variés sont apparus sur les sites Web, confirmant ainsi l'évolution démographique des communautés francophones en situation minoritaire au Canada.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".