Emploi des anglicismes par les adolescents et les jeunes adultes dans les SMS : comparaison entre le Québec et la Suisse
Bibliographic record
Abstract
This research project is based on a sociolinguistic approach and presents a comparison between Quebec French and Swiss French of anglicisms in SMS messages made by teenagers and young adults. Using two sub-corpora, one Quebecer sub-corpora and one Swiss sub-corpora, both provided by the sms4science project, we selected the 12 to 25 year old group. In order to identify the anglicisms, we chose the Office québécois de la langue française (OQLF) categorization: lexical borrowing (anglicisme intégral), hybrid borrowing (anglicisme hybride), semantic borrowing (anglicisme sémantique), syntactic borrowing (anglicisme syntaxique), morphological borrowing (anglicisme morphologique) and phraseological borrowing (anglicisme phraséologique). The results reveal that, of all six categories of anglicisms, the lexical borrowing is the most used by both Quebecers and Swiss and that the 18 year olds and the 21 year olds are most prone to use anglicisms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".