Shoule Québec Rename Its Language? A Diachronic Analysis of Québécois French
Bibliographic record
Abstract
Canadian French has evolved away from metropolitan French in vocabulary, accent, slang, and even grammar structures since it was colonized in the 16th century. In analyzing the development of the Québécois language, this thesis aims to provide insights as to whether renaming Canadian French that is spoken in the province of Québec to Québécois would better represent the culture and people who use the language. This thesis includes an analysis of the history of Québec from its colonization by France, the legislation in place to protect the languages of French and Québécois, and an analysis of some of the linguistic and cultural differences between metropolitan France and Québec. This research was completed using a variety of sources, from research papers to government documents, to provide insights into how far Québécois French has strayed from metropolitan French. The aim of this paper is not to debate whether Québécois is different from metropolitan French. This is a known fact. Instead, it aims to answer the question of whether the language is different enough to warrant consideration to rename the language.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".