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Record W4382893638 · doi:10.15460/apropos.10.1981

Da(ny) goes (auto)graphic

2023· article· fr· W4382893638 on OpenAlexaboutno aff
Anne Brüske

Bibliographic record

Venueapropos [Perspektiven auf die Romania] · 2023
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Dans ma contribution, je me propose d’étudier la question de l’adoption de nouvelles formes médiales chez Laferrière qui l’amène à recourir au genre hybride du roman graphique, situé à mi-chemin entre littérature et art visuel. Partant de l’exemple de Vers d’autres rives (2019), mon analyse portera sur la fonction de ce revirement pour le projet laferrien et sur les déplacements qui en résultent pour la relation entre la production autofictionnelle et son positionnement par rapport à différents espaces et différentes villes. Comment le discours des romans graphiques évolue-t-il en ce qui concerne l’espace et l’appartenance culturelle de l’artiste ? Pour répondre à de telles questions, je présenterai premièrement l’œuvre autofictionnelle de Laferrière pour ensuite situer ses « romans dessinés » dans le contexte québécois et haïtien, et partagerai enfin quelques réflexions concernant le récit « autographique » (Whitlock 2006) ainsi que la façon dont il construit, par le biais de l’écriture et des images, l’espace social et médial du récit. La dernière partie sera consacrée à l’analyse de Vers d’autres rives sous l’angle de l’autoreprésentation, des espaces socioculturels et de l’apport de l’intermédial aux réflexions autofictionnelles, spatiales et poétologiques de Laferrière.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.223
Threshold uncertainty score0.747

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2230.046

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 head0.039
GPT teacher head0.285
Teacher spread0.246 · 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
Published2023
Admission routes1
Has abstractyes

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