Bibliographic record
Abstract
Bien avant l’heure des écrans, l’écrivain et la machine se rencontraient déjà autour d’objets comme la machine à écrire, ou plus tard, la ronéotypeuse et la photocopieuse. Dans cet article, on prend le parti de faire machine arrière pour explorer la manière dont les écrivains aspirant à l’indépendance éditoriale, tout au long du XXᵉ siècle, ont utilisé les machines de la bureautique pour publier et diffuser eux-mêmes leurs propres ouvrages. On s’arrête en particulier sur le cas du fanzine, forme incontournable de l’autoédition, pour analyser les manières dont les auteurs se sont emparés des machines à leur disposition pour ruser avec les instances traditionnelles de l’autorité et de la légitimation littéraires. Dans un dernier temps de la réflexion, on s’interroge sur les liens complexes que nouent ces pratiques « papier » avec les renouvellements numériques de l’autoédition.
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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".