Étude diachronique du discours normatif sur les anglicismes dans les chroniques de langue au Canada francophone : d’Alphonse Lusignan à Guy Bertrand
Bibliographic record
Abstract
Cette tude se penche sur le traitement des anglicismes dans six chroniques de langue vise normative publies entre 1884 et 2018. Cent emplois comments ont t analyss pour chaque chronique, pour un total de 600. Nous avons vrifi si une volution dans le temps tait perceptible pour les lments suivants : dans quelles proportions les anglicismes font-ils l'objet d'un commentaire par rapport aux autres sujets abords ? Certains types d'anglicismes soulvent-ils plus de questions que d'autres ? Le jugement normatif sur les anglicismes est-il ngatif, positif ou neutre ? Quels arguments sont voqus pour condamner un anglicisme ? Il ressort de cette tude que les anglicismes demeurent un sujet de proccupation normative chez les chroniqueurs de langue, les deux plus contemporains les abordant davantage que leurs prdcesseurs, et celui qui signe la chronique la plus rcente les condamnant davantage que les autres du corpus.
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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 | 0.003 | 0.005 |
| 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 | 0.006 |
| Scholarly communication | 0.005 | 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".