L'Esprit d'Albertine: le personnage de roman à l'ère de la vitesse moderne
Bibliographic record
Abstract
The subject of this thesis is the novel character during the emergence of modern speed, that is to say between the transportation revolution, which began around the mid-nineteenth century, and the first third of the 20th century. Our hypothesis is that the transformations affecting speed during this period gave rise to new types of characters – such as the passer-by, the passenger, the individual in a hurry or lost in some transit area – whose presence in the novel is in passing. In developing this idea, we use a character which, in itself, embodies all of the issues raised by the introduction of modern speed in novels. This character is Albertine Simonet, the "budding girl" of À la recherche du temps perdu by Marcel Proust. Albertine indeed hold a highly strategic position for our subject matter. In the "inter-century" work that is À la recherche du temps perdu (as described by Antoine Compagnon), she draws to herself the modern elements revealed by Balzac and Baudelaire – the modernity of passers-by, crowds and anonymity in large cities, which were all outward signs of modern speed before the means to make it a reality even appeared –,while truly being a woman of her time, as a contemporary of significant technical inventions, to which she is continually associated in Proust's novel. Whether used as an introduction or as a means of comparison, Albertine is a guide for our analysis and preludes the traveler characters of Octave Mirbeau, Paul Morand and Valery Larbaud, whose peculiarity resides in that their adventure dissolves in its own movement.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".