Bibliographic record
Abstract
Nous avons essaye d'analyser les caracteres du francais canadien en retracant l'histoire de la langue francaise au Canada. En passant du Regime francais et du Regime britannique jusqu'aux 'joualeux' de nos jours, nous pouvons dire ici qu'ils combinent, d'une part des survivances et d'autre part, des innovations. Les remarques qu'ils apportent sur la colonisation nous eclairent l'histoire des regionalismes et des archaismes. La societe canadienne-francaise qui avait ete longtemps en majorite agricole, s'urbannise peu a peu. En 1763, dans la colonie de la Nouvelle France il y avait 70000 citoyens francophones dont 5000 seulement qui voulaient partir pour la France. Les 65000 francophones qui se sont decides a rester au Canada, grace a eux, c'est la raison essentielle que Le Canada devient un pays bilingue. Ils ont eu le sentiment d'appartenance au Canada. Le sentiment d'appartenance a cree le sentiment independant et l'identite canadienne. C'est ainsi que Le Canada devient officiellement l'organisme du bilinguisme en 1967, 100 ans apres la confederation. En guise de conclusion a cette etude du francais au Canada, nous resumerons ici notre opinion comme le regionalisme, l'archaisme, le canadianisme et le bilinguisme.
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 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 | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.004 |
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".