Bibliographic record
Abstract
Que nous disent les archives des maisons d’édition sur le livre, sur sa conception, sa fabrication et sa diffusion ? Ce livre collectif est le premier à se pencher sur le corpus pourtant considérable des archives éditoriales canadiennes, françaises, belges et suisses. Les articles ici rassemblés proposent des parcours d’exploration dans des fonds d’archives des XIXe et XXe siècles, de Tournai à Montréal, de Lausanne à Paris. À la lumière des documents d’archives se révèlent les relations de pouvoir et de collaboration entre la direction et les employé-es des maisons d’édition, les concurrences et les collaborations entre les éditeurs ainsi que les négociations avec les agents de la chaîne du livre, de l’imprimeur au libraire. Abordant une variété de secteurs (la littérature pour enfants, l’édition de sciences humaines ou encore l’édition militaire), ce livre suit les traces de l’histoire du livre : ces traces souvent inaperçues et pourtant très matérielles que conservent les archives éditoriales.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".