Bibliographic record
Abstract
Base de données de l’Atlas sonore des variétés de français au Canada. Ces données sont constitués d'enregistrements libres, où les participants partagent leur réalité en tant que francophones au Canada. <br><br> Ce projet vise à valoriser les différents accents de la francophonie canadienne et à les situer géographiquement. Vous pouvez voyager avec votre curseur d’un coin à l’autre du pays en écoutant les différents accents. <br><br> Un de nos objectifs est aussi d’offrir un outil pédagogique pour les enseignant·e·s et les élèves intéressé·e·s par le français, la diversité et la variation linguistique. <br><br> Ce projet est une co-création de Dre Marie-Eve Bouchard et Dre Amanda Cardoso de l’Université de la Colombie-Britannique. Il a été financé par Language Science Institute et Open Educational Resources Fund de l’Université de la Colombie-Britannique.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.009 |
| Science and technology studies | 0.012 | 0.000 |
| Scholarly communication | 0.013 | 0.001 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.008 |
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".