Bibliographic record
Abstract
Qu’est-ce que lire en moderne ? Walter Benjamin définit l’homme moderne, et donc aussi le lecteur moderne, comme un « caractère traumatophile ». Jules de Gaultier, le théoricien du bovarysme, compare Mme Bovary, la fameuse héroïne lectrice de Flaubert, à un artiste contraint à l’inachèvement, qui échoue à insuffler la vie à l’idéal qu’elle trouve dans les livres. Dans cet article, j’explore le cas de Georges Perec lecteur de Raymond Roussel dans un essai initulé Roussel et Venise. Esquisse d’une géographie mélancolique. Puis je m’intéresse à Perec à la fois auteur et lecteur de W, cette fiction inachevée inscrite dans un contexte autobiographique qui en dévoile l’origine traumatique. Je m’efforce de montrer que l’œuvre de Perec s’adresse à un lecteur qui lui ressemble : ce lecteur moderne, mélancolique, qui doit faire le deuil de l’achèvement. Georges Perec and the Mourning for Completion ABSTRACT What is modern reading? Walter Benjamin defines the modern man, and thus the modern reader, as a “traumatophilic type”. Jules de Gaultier, the theoretician of bovarism, compares Mrs Bovary, the famous Flaubertian reading hero, to an artist constrained to incompletion, who fails to bring the ideal she finds in books to life. In this article, I explore the case of Georges Perec as reader of Raymond Roussel in an essay entitled Roussel and Venice. Outline of a Melancholic Geography. Secondly, I focus on Perec as both author and reader of W, an incomplete fiction included in an autobiographical context which reveals its traumatic origin. I attempt to show that the work of Perec is for a reader who is similar to him: a modern, melancholic reader who mourns for completion.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".