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Record W4407721112 · doi:10.7202/1115974ar

<i>Victoria K, Delphine Seyrig et moi ou La petite chaise jaune</i> : un matrimoine en conversion d’archives

2024· article· fr· W4407721112 on OpenAlexvenueno aff
Noha Nemer, Valérie Cachard

Bibliographic record

VenuePercées Explorations en arts vivants · 2024
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

Le texte lauréat du Prix RFI Théâtre (2019) Victoria K, Delphine Seyrig et moi ou La petite chaise jaune (2021) de Valérie Cachard s’inscrit dans la mouvance de la « littérature hors du livre » (Rosenthal et Ruffel, 2010 : 4), où l’auteur·trice légitime la réception de son texte à travers une performance narrative. Après avoir interrogé la nature et le bien-fondé des archives intimes de Victoria K, lettres extraites de son journal intime abandonné dans sa maison, l’article s’intéresse aux allers-retours entre la fiction et le réel fictionnel qui systématisent une mémoire solidaire de la guerre civile en apparence fragmentaire. La performance du texte à Beyrouth par la dramaturge et son acolyte artistique Hadi Deaibes tend à éroder les dimensions sociopolitiques de l’archivage au profit d’une hybridation des identités scéniques. Cette contribution, coécrite par Noha Nemer et son amie de longue date Valérie Cachard, propose une réflexion sur l’expropriation discursive, esthétique et scénique d’une littérature intimiste.

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)0.003
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 score0.275
Threshold uncertainty score0.546

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.011
Scholarly communication0.0110.003
Open science0.0010.005
Research integrity0.0020.004
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 head0.021
GPT teacher head0.257
Teacher spread0.236 · 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
Published2024
Admission routes1
Has abstractyes

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