Bibliographic record
Abstract
La pandémie de Covid-19 a donné lieu à une explosion de néologismes pour désigner dans les différentes langues les nouvelles réalités qui apparaissent tous les jours à l'échelle mondiale.Entre flottement de l'usage et prises de position normatives, le genre de Covid-19 est au cœur d'une polémique largement relayée dans les médias.À partir d'un corpus d'articles de presse européens et canadiens francophones, cette contribution vise à identifier les arguments avancés par les différentes parties et à montrer comment les variables linguistiques, idéologiques et sociales s'articulent dans le discours de presse.Notre analyse rend compte de la complexité de ce débat dans lequel de nombreux paramètres interviennent : le rapport des francophones à l'emprunt en général et aux anglicismes en particulier, le bras de fer entre usage et norme, la légitimité et la diffusion des discours de référence, la variation interne au français et les préférences morphosyntaxiques des deux côtés de l'Atlantique.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".