Lexical obsolescence of French loanwords in Canadian English
Bibliographic record
Abstract
The purpose of this study is to present a refined classification of Canadianisms of French origin that have fallen out of use but have not been identified as obsolete in the second edition of the “Dictionary of Canadianisms on Historical Principles”, taking into account the causes of their obsolescence, as well as their frequency and association with a particular semantic field. The article examines 169 Gallicisms extracted from the dictionary, with their subsequent distribution into frequency categories (based on their use in the three Canadian media outlets – “The Globe and Mail”, “Montreal Gazette”, “CBC”) and 14 semantic fields. The scientific novelty of the research lies in the fact that it presents, for the first time, a subject-related classification based on the frequency of occurrence for obsolete borrowed Canadianisms and a detailed discussion of the underlying causes of their obsolescence. The results of the study show that the lexical obsolescence of these loanwords is mainly due to extralinguistic factors. Many of the French-derived Canadianisms refer to still-existing realities of Canada, such as wildlife or geographical features. They therefore do not qualify for the most common classification as either archaic (they have no single-word equivalent) or historical (they express realities that still exist today). Since these obsolete words highlight a conceptual change in perception due to the loss of relevance of certain ways of life, they can be categorised as notiolisms.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".