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Record W3212585427 · doi:10.32725/eer.2020.012

Creating at the crossroads of cultures: La chair du maître by Dany Laferrière and its film adaptation by Laurent Cantet

2020· article· fr· W3212585427 on OpenAlexaboutno aff
Katarzyna Wójcik

Bibliographic record

VenueÉcho des études romanes · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicDiverse multidisciplinary academic research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

La littĂŠrature et le cinĂŠma peuvent être considĂŠrĂŠs comme terrain d'ĂŠchanges transnationaux aussi bien au niveau de la fiction que celui de la crĂŠation artistique. Le recueil de nouvelles La Chair du maĂŽtre (1997) de Dany Laferrière - ĂŠcrivain quĂŠbĂŠcois d'origine haïtienne - est un des exemples de cette crĂŠation littĂŠraire qui traverse les frontières nationales et inscrit des expĂŠriences d'une autre culture dans le champ littĂŠraire quĂŠbĂŠcois. Le texte de Laferrière a servi d'inspiration au rĂŠalisateur français Laurent Cantet qui a mis sur l'ĂŠcran des nouvelles choisies pour rĂŠaliser le film Vers le sud (2005). En plus d'être une transposition filmique d'une œuvre littĂŠraire « transnationale », le film de Cantet, coproduction franco-canadienne, est lui-même une pratique artistique qui dĂŠpasse les frontières entre les cultures. À travers l'analyse de cette œuvre de Laferrière et les modifications qui dĂŠcoulent de son adaptation filmique, l'article se propose d'interroger l'image que les deux crĂŠations proposent de deux communautĂŠs culturelles - haïtienne et nord-amĂŠricaine (i.e. quĂŠbĂŠcoise) - ainsi que la façon dont elles problĂŠmatisent les contacts entre les cultures. L'image de ceux-ci est construite par les choix au niveau de l'intrigue et de l'ĂŠnonciation de l'adaptation ainsi que par les relations intertextuelles (et interdiscursives) qu'elle entretient avec l'imaginaire filmique et pictural europĂŠen.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.044
GPT teacher head0.323
Teacher spread0.279 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2020
Admission routes1
Has abstractyes

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