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Record W2736705009 · doi:10.15388/litera.2006.4.8051

Pažadėtosios žemės motyvas Antonine’os Maillet romane “Pelaži vežėčios”

2015· article· fr· W2736705009 on OpenAlexaboutno aff
Vytautas Bikulčius

Bibliographic record

VenueLiteratūra · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

L’écrivaine du Canada Antonine Maillet (née en 1929) a obtenu la célébrité avec son roman «Pélagie-la-Charrette» qui en 1979 a reçu le plus prestigieux prix littéraire de France – le prix Goncourt. Dans le roman l’auteure se retourne au passé du Canada où en 1775 les troupes du roi George sont venues déloger de chez eux les Acadiens de la baie Française. Parmi les exilés il y avait une certaine Pélagie Bourg qui ayant passé plusieurs années de misère en exil, a acheté une charrette et une paire de boeufs et a commencé son retour à la baie Française. Comme ce voyage sort du cadre d’un héros ou d’une famille et se lie avec plusieurs Acadiens, il obtient un caractère universel et les liens du roman avec la Bible surgissent. Comme Pélagie devient initiatrice de ce retour, autour d’elle se rassemblent les Acadiens et elle rappelle le personnage Moïļse qui menait aussi son peuple à la Terre promise. A la fin du roman le motif de la Terre promise obtient un aspect imprévu parce que les gens qui sont revenus avec elle sont devenus comme un peuple.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.980
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0290.007

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 head0.026
GPT teacher head0.241
Teacher spread0.215 · 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
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
Published2015
Admission routes1
Has abstractyes

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