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Record W7033311367

Portrait de villes littéraires : Moncton et Ottawa

2013· other· en· W7033311367 on OpenAlexvenueaboutno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2013
Typeother
Languageen
FieldEnvironmental Science
TopicPublic Health and Environmental Issues
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)FrenchOrder (exchange)PrestigeCanadian literaturePortrait
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores the cities of Moncton and Ottawa as "literary capitals," a concept developed by Pascale Casanova. While Moncton has managed to become the literary capital of Acadie, Ottawa, which resembles its Acadian counterpart in many ways, struggles to endorse this function for Francophone Ontario. Each part of this thesis examines the institutional role of these cities and identifies the writing strategies by which their authors have tried to turn them ‒ or not ‒ into literary capitals.The first chapter focuses on Moncton in Moncton mantra by Gérald Leblanc and in Petites difficultés d'existence by France Daigle, and the second, on Ottawa in La Côte de Sable by Daniel Poliquin and in King Edward by Michel Ouellette. The conclusion puts forward hypotheses as to why Ottawa has failed to become a literary capital in the way that Moncton has while reassessing the concept in the context of exiguity. By adopting, in order to distance themselves from the literature of Sudbury, an aesthetic that does not emphasis spatial representation, authors from Ottawa are unable to contribute to the literary prestige of their city. Ottawa remains nonetheless the institutional centre of Francophone Ontario, and a literary city.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.087
Threshold uncertainty score0.327

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0170.008
Scholarly communication0.0060.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.002
GPT teacher head0.150
Teacher spread0.148 · 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 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
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueLibrary and Archives Canada (Government of Canada)→Same topicPublic Health and Environmental Issues→French-language works237,207→