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Record W27354103 · doi:10.1016/j.gie.2016.06.046

La reception du roman au Quebec et au Canada anglais dans les annees mille neuf cent cinquante

2007· dissertation· fr· W27354103 on OpenAlexaboutno aff
Andréanne Lechasseur-Pierre

Bibliographic record

VenueGastrointestinal Endoscopy · 2007
Typedissertation
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsSubjectivityIdeologyInstitutionArtHumanitiesFrenchLiteraturePhilosophyArt historyLawPolitical scienceEpistemology

Abstract

fetched live from OpenAlex

What is a classic ? To this day, no consensus exists on the definition of the literary classic , or on the definition of canon. It is an open debate, to which this master thesis participates. For many centuries, classics were selected for various aesthetic criteria that seemed to go 'without saying', and that scholars did not feel the need to justify. During the second half of the twentieth century however, views on the concept began to change. Debates emerged on the universality of its definition, and the idea that subjectivity might govern its selection process started to be examined. The literary Institution, as presented by Jacques Dubois, became for most critics the main agent of canonization, and aesthetic was demoted to a factor amongst others. Still, whether we are discussing canonic genre or ideology, we are forced to admit that the Institution does not discriminate its classics the same way everywhere. Of all those elements of subjectivity now taken into consideration in the field of canonical studies, it is the cultural aspect of the process that interests us here, and more precisely its manifestation in French and English Canada. By examining the critical reception of six Canadian classics published in the 1950's, we hope to find how those novels gained their recognition, and therefore shed some light on the Canadian way of envisioning the literary canon.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.258
Teacher spread0.246 · 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.

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
Published2007
Admission routes1
Has abstractyes

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