Bibliographic record
Abstract
Certains elements du francais quebecois ont infiltre, colore, enrichi la langue de la litterature canadienne-francaise des le debut de son histoire. Il s’agit de mots et de locutions qui sont censes appartenir au francais particulier de ce pays, que l’on appalle d’habitude des quebecismes, mais dont les auteurs se servent quand meme dans leur propre discours de narrateur. Ce geste autorise a croire qu’ils les consideraient comme faisant partie du langage correct, c’est-a-dire juge correct par l’elite intellectuelle pendant une periode donnee de l’histoire (litteraire) du Quebec, et que l’on appelle communement le bon usage. L’emploi de ces expressions leur permet aussi de manifester leur solidarite avec elles, ou, au contraire, leur desapprobation lorsqu’ils ne les emploient que dans des dialogues. Le Glossaire qui suit l’Introduction compte 693 unites lexicales, et propose l’analyse historique et stylistique de 928 usages, certaines unites en ayant plusieurs. Les textes depouilles embrassent l’essentiel de la litterature canadienne-francaise d’avant la Revolution tranquille.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".