Bibliographic record
Abstract
Cet article étudie la gestion, par cinq rédactions en ligne belges, des commentaires que les internautes postent au sujet de la langue des journalistes.Trois questions sont posées : ces commentaires sur la langue sont-ils visibles ou sont-ils filtrés par les rédactions ?Engendrent-ils des corrections dans les articles journalistiques ?Quelles réactions suscitent-ils chez les administrateurs ?Internautes et administrateurs semblent partager une sorte d'« idéologie du sans faute » en matière de langue.Néanmoins, les contraintes professionnelles des journalistes en ligne les empêchent, selon eux, d'atteindre leur idéal linguistique.Bien que la « relecture » des internautes profite aux rédactions dans une certaine mesure, l'empreinte linguistique des commentaires d'internautes, tant du point de vue de leur visibilité que de leur influence, est limitée par le désintérêt que portent les rédactions à la gestion des commentaires.
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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".