Bibliographic record
Abstract
A la suite de l'etude sur les caracteres generaux du francais canadien, nous avons essaye de degager ses caracteres linguistiques dans cette etude. Nous avons choisi le francais ontarien et acadien comme echantillon d'analyse, parce que ce sont les deux francais qui ont les caracteres representatifs parmi les francais canadiens parles hors Quebec. La problematique importante du francais canadien hors Quebec sont due au transfert et a la restructuration. Les conditions d'acquisition et d'utilisation du francais dans les communautes canadiennes-francaises minoritaires nous montre beaucoup de restrictions. Nous avons trouve la specificite de locuteurs qui comprend, une partie, des vieux francophones unilingues et, l'autre, des jeunes qui s'expriment bien en anglais pour peu pratiquer le francais a la maison. A ce point-la, nous pouvons prevoir la direction de l'evolution diachronique du francais canadien. Meme aujourd'hui, on peut constater que ce francais est tres influence par l'anglicisme. C'est ainsi que les deux communautes francophones minoritaires resistent a l'usage de l'anglais dans la vie quotidienne. Compte tenu de la variete de situation dans laquelle se trouve le francais canadien hors Quebec, ce genre d'etude montre que le francais evolue synchroniquement par la diversite situationnelle.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.003 |
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".