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Record W3029909171 · doi:10.7202/1068994ar

TUER ENTRE NOUS

2020· article· fr· W3029909171 on OpenAlexaffvenue
David Bélanger, Cassie Bérard

Bibliographic record

VenueVoix et Images · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversité du Québec à MontréalMcGill University
Fundersnot available
KeywordsHumanitiesIdiotPhilosophyArtLiterature

Abstract

fetched live from OpenAlex

Cet article s’intéresse au « retour » que fait le régionalisme, celui idyllique du début du xxe siècle, dans la littérature québécoise récente. Ce retour, plus précisément, rend compte de crimes dans un univers sachant difficilement les contenir. Dans Le discours sur la tombe de l’idiot (2008) de Julie Mazzieri, Le chasseur inconnu (2014) de Jean-Michel Fortier et Trois fois la bête (2015) de Zhanie Roy, nous rencontrons effectivement des meurtres, sans que les infrastructures ne permettent de les traiter : ni enquêteur, ni médecin légiste, ni quelque instance judiciaire n’apparaissent dans ces fictions. Une telle représentation du crime permet de conceptualiser ces oeuvres comme des « actualisations à distance », c’est-à-dire que le mouvement de retour s’avère sciemment problématisé selon les conceptions éthiques contemporaines. Par le biais des questions de l’origine et de l’autorité, comme interrogations au coeur de ces fictions critiques de l’idéal régionaliste, cet article entend éclairer ce geste de création important dans la production récente.

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)0.005
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 score0.491
Threshold uncertainty score0.988

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.012
Scholarly communication0.0090.005
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0590.011

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 head0.016
GPT teacher head0.240
Teacher spread0.224 · 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
Published2020
Admission routes2
Has abstractyes

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