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Record W2520317196 · doi:10.20381/ruor-5399

Le mal du pays: nostalgie et retour aux sources dans les contes de Fred Pellerin

2016· dissertation· fr· W2520317196 on OpenAlexaboutno aff
Stéphanie Roussel

Bibliographic record

VenueuO Research (University of Ottawa) · 2016
Typedissertation
Languagefr
FieldSocial Sciences
TopicDiverse multidisciplinary academic research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Cette thèse de maîtrise est une analyse du concept du retour dans les trois premiers recueils de contes publiés par Fred Pellerin : Dans mon village, il y a belle Lurette… (2001), Il faut prendre le taureau par les contes! (2003) et Comme une odeur de muscles (2005). L’objectif est de démontrer que la nostalgie pour le passé et le désir du retour aux sources représentent un concept qui revient à plusieurs reprises dans les contes de Pellerin et qu’il suscite un engouement chez ses lecteurs. En ce qui a trait à la méthodologie, cette thèse se divise en deux grandes parties intitulées respectivement « Les grands thèmes » et « Langue et procédés techniques ». La première partie porte sur l’analyse des différents motifs qui font partie intégrante de l’ensemble de l’oeuvre de Fred Pellerin: les thèmes du refuge, de la solidarité, du village, de l’histoire et du passé seront, entre autres, analysés. La deuxième partie étudie les particularités de la langue de l’auteur. L’histoire de la langue française au Québec, les niveaux de langage et les procédés techniques sont les principaux éléments qui caractériseront cette partie du travail.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.105
GPT teacher head0.375
Teacher spread0.271 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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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