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Record W4200516079 · doi:10.26522/vp.v18i2.3539

exil, entre terre et mer : le mouvement dans Les litanies de l’Île-aux-Chiens de Françoise Enguehard

2021· article· fr· W4200516079 on OpenAlexvenueaboutno aff
Juliette Valcke

Bibliographic record

VenueVoix Plurielles · 2021
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Originaire de l’archipel de Saint-Pierre-et-Miquelon, Françoise Enguehard vit actuellement à Terre-Neuve, soit à une dizaine de milles marins de son lieu de naissance. C’est dans son amour pour celui-ci et dans la volonté d’accomplir un devoir de mémoire à l’égard des générations futures qu’elle a puisé l’inspiration pour Les litanies de l’Île-aux-Chiens (1999), roman dans lequel elle fait revivre ses grands-parents, Victor et Marie-Joseph Lemétayer, partis de Bretagne en 1899 dans l’espoir de trouver une vie meilleure à Saint-Pierre. Le présent article vise à montrer que ce roman, par son exploitation du motif du mouvement, participe pleinement de l’histoire littéraire transatlantique, qui repose elle-même sur l’idée de rencontres et d’échanges provoqués par la migration. Multiforme, ce motif se retrouve en effet au cœur même de l’intrigue tout en exerçant son empreinte sur d’autres aspects de l’œuvre ; paratexte, structure, thématique, procédés stylistiques en sont notamment tributaires, parachevant cette poétique de la mouvance si particulière de l’auteure saint-pierraise.

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)0.001
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: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.500

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.012
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.264
Teacher spread0.239 · 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
Published2021
Admission routes2
Has abstractyes

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Same venueVoix PluriellesSame topicLinguistics and Discourse AnalysisFrench-language works237,207