Bibliographic record
Abstract
Cet article porte sur la gestion du temps de la semaine dans les hebdomadaires d’information qui connaissent le risque d’avoir un temps de retard, par rapport aux quotidiens et aux autres médias (radio, télévision). L’article présente les deux modèles historiques français d’hebdomadaires d’information, les « hebdomadaires de lecture » et les « miroirs photographiques » jusqu’à l’instauration en 1964 du format newsmagazine . Il montre les procédés poétiques inventés par les hebdomadaires pour concurrencer avec succès les quotidiens et les autres médias : événementialisation, éditorialisation, illustration. Il insiste enfin sur la présence à côté de l’actualité hebdomadaire d’une semaine cycle avec un traitement de l’actualité récursif qui accompagne les nouveaux rythmes collectifs et professionnels, qui construit des communautés et véhicule des styles de vie.
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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.028 | 0.010 |
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".