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Record W2580343530 · doi:10.7202/1038500ar

Voix d’eau : Pascal Quignard et « la voix perdue » des lais bretons

2016· article· fr· W2580343530 on OpenAlexvenueno aff
Nathalie Koble, Adriana Nicolau

Bibliographic record

VenueTangence · 2016
Typearticle
Languagefr
FieldArts and Humanities
TopicMedieval European Literature and History
Canadian institutionsnot available
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

Les liens que l’oeuvre de Pascal Quignard entretient avec la littérature médiévale sont à la fois discrets et multiples, au sein d’une écriture de part en part travaillée par la confrontation à de multiples univers esthétiques et littéraires. Élaboré par l’écrivain contemporain, le concept de « jadis », d’inspiration lacanienne, engage néanmoins une réflexion sur la mémoire qui entretient avec le Moyen Âge perdu des contes, mais aussi, avec la conception médiévale de la mémoire littéraire, une résonance particulière. Cette étude se propose de mettre au jour cette résonance en confrontant deux récits qui reposent sur une intrigue en grande partie similaire : « La voix perdue » de Quignard et le lai anonyme de Tydorel. Cette lecture croisée met en évidence une réflexion en miroir sur l’inaccessibilité de l’origine, figurée dans les deux textes par des lieux/personnages aquatiques. Antérieure à la langue, cette origine fantasmée est dans les deux contes au coeur d’une poétique du détour qui tente de cerner, par la langue littéraire, les eaux les plus troubles de la rencontre amoureuse.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.009
Scholarly communication0.0050.003
Open science0.0000.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.025
GPT teacher head0.246
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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
Published2016
Admission routes1
Has abstractyes

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