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Record W7067151632

L'Esprit d'Albertine: le personnage de roman à l'ère de la vitesse moderne

2011· other· en· W7067151632 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2011
Typeother
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsCharacter (mathematics)Subject (documents)AdventureModernityPeriod (music)AnonymityCrowds
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.711
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.006
GPT teacher head0.178
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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Same venueLibrary and Archives Canada (Government of Canada)Same topicLibrary Science and AdministrationFrench-language works237,207