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Record W4317773680 · doi:10.32725/eer.2022.029

Dany Laferrière's universes: Paris-novel

2023· article· fr· W4317773680 on OpenAlexaboutno aff
Květuše KUNEŠOVÁ

Bibliographic record

VenueÉcho des études romanes · 2023
Typearticle
Languagefr
FieldArts and Humanities
TopicLiterature and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSoulMiamiThe ImaginaryArt historyArtSociologyLiteraturePhilosophyTheologyPsychoanalysisPsychology

Abstract

fetched live from OpenAlex

En):In the novel Autoportrait de Paris avec chat (Boréal, 2018), Dany Laferrière, writer from the periphery, reaches the centre.The article is a questioning of the universe or rather the universes (and their centres) that Dany Laferrière creates in his texts."My heart is in Port-au-Prince, my body in Miami and my soul in Montreal" -he said several times during interviews 1 .The analysis of the novel Autoportrait de Paris avec chat questions Laferrière's relationship with Paris, which represents a new anchor point in his life.By considering Paris less a city than a "novel", Dany Laferrière transcends geographical and linguistic as well as literary and artistic borders.Time is erased in his vision of the city, the many faces of which are brought up to date.In the author's eyes, Paris reappears as an imaginary centre and a source of inspiration for literary authors and artists since the Middle Ages.The purpose of the article is to demonstrate in what sense this Parisian "drift" opens up new perspectives to the message of Laferrière's work.In his text, Paris reveals itself as a universal, historical and mythical city, but also a place that can rejuvenate and reborn, a centre of hope and of the future.

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)0.002
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.013
Scholarly communication0.0110.004
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.033
GPT teacher head0.243
Teacher spread0.210 · 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
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
Published2023
Admission routes1
Has abstractyes

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