Qu’ont en commun Mimi Estival, Roxanne d’Avril et Georgette Mars? Auctorialité et roman sentimental québécois de l’après guerre (1944-1965)
Bibliographic record
Abstract
Des années 1940 au milieu des années 1960, le Québec a assisté à l’essor des collections de romans populaires publiés en fascicules, écrits par des auteurs locaux et se déroulant dans La Belle Province. Signés d’une multitude de pseudonymes, ces objets sont extrêmement révélateurs du fonctionnement de l’auctorialité, sous le mode de la lecture sérielle. En s’intéressant à la collection « Roman d’amour » des Éditions Police-Journal, cet article souhaite explorer plus spécifiquement le fonctionnement du nom d’auteur en lien avec le pacte de lecture établi par le roman sentimental. --- From the 1940s to the mid-1960s, Quebec witnessed a boom in series of popular novels published in instalments, written by local authors, and set in La Belle Province. Appearing under a multitude of pseudonyms, these books tell us a great deal about the workings of authorship in the reading of serialised publications. In its examination of the series “Roman d’amour” put out by Éditions Police-Journal, this article seeks to explore in a more specific way how the author’s name functions in relation to the reading contract established by the genre of the romance novel.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".