Journalisme culturel en mutation
Bibliographic record
Abstract
Le Dossier analyse les pratiques éditoriales du journalisme culturel. La rubrique Échanges poursuit une discussion sur la notion d’« acceptabilité sociale » dans le cadre de la pandémie de Covid-19 et au-delà. Les cinq Notes de recherche portent sur les témoignages relatifs aux attentats du 13-Novembre, le traitement des podcasts dans la presse, la consommation des séries, le rôle de Twitter dans les dénonciations de l’inceste et, enfin, les discours d’influenceuses contre les mesures sanitaires au Québec. En VO offre un article en langue anglaise sur l’insertion des codes du jeu dans la présentation des informations. Le Focus revient sur Cybernétique et société de Norbert Wiener. Pour leur part, les Notes de lecture rendent compte de plus de 50 publications. The Issue section analyses editorial practices in cultural journalism. The Exchange section continues a discussion on the notion of 'social acceptability' in the context of the Covid-19 pandemic and beyond. Five Research Notes look at testimonies relating to the attacks of 13 November, treatment of podcasts in the press, consumption of series, the role of Twitter in calling out incest and, finally, the discourse of female influencers against health measures in Quebec. En VO offers an English-language article on the use of gaming codes in the presentation of news. The Focus section returns to Norbert Wiener's Cybernetics and Society. Reading Notes cover more than 50 publications.
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 | 0.013 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.035 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".