MétaCan
Menu
Back to cohort
Record W1936061652 · doi:10.7202/1032634ar

La médiation intertextuelle

2015· article· fr· W1936061652 on OpenAlexvenueaboutno aff
André Lamontagne

Bibliographic record

VenueVoix et Images · 2015
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

La vie provisoire et À quoi ça rime ? ont en commun un parcours diégétique qui s’ouvre sur une scène extraterritoriale (respectivement la République dominicaine et le Portugal), retourne à Montréal et se déplace dans les Laurentides, lieu de retraite et d’ermitage littéraire. Dans chacun des deux romans, le personnage central fait une multitude de deuils (oncle, épouse, ami, relations amoureuses, vie antérieure) et aspire au détachement, à devenir autre. Cette découverte de l’autre en soi prend une dimension hautement intertextuelle : le protagoniste de La vie provisoire lit et relit les auteurs russes dans son refuge et invente un conte sur le modèle des Mille et une nuits, tandis que le narrateur d’À quoi ça rime ? suit les traces de Fernando Pessoa (lui-même connu pour ses hétéronymes) dans Lisbonne et cherche des vecteurs identitaires dans la littérature. Cet article se propose d’étudier la représentation de la lecture dans les deux derniers romans d’André Major : ses modalités et ses dispositifs intertextuels, ses incidences diégétiques et son potentiel d’altérité. Comme le montre l’auteur, l’acte de lire prolonge l’axe thématique des oeuvres antérieures de l’écrivain, ainsi l’idée de désertion, et reprend certaines questions récurrentes de la littérature québécoise, notamment les oppositions vie-écriture (Réjean Ducharme, Jacques Godbout) et nature-culture (Louis Hamelin).

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0060.021
Scholarly communication0.0170.016
Open science0.0020.011
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0330.006

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 head0.053
GPT teacher head0.316
Teacher spread0.264 · 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 designTheoretical or conceptual
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
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueVoix et ImagesSame topicLinguistics and Discourse AnalysisFrench-language works237,207