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Record W7125666193

Anonymous extras and figures archived in the painter's garden : getting space of a multiple painting and invention of territory

2019· article· fr· W7125666193 on OpenAlexaboutno aff
Léon-Claude Chiche

Bibliographic record

Venuetheses.fr (ABES) · 2019
Typearticle
Languagefr
FieldArts and Humanities
TopicArt, Politics, and Modernism
Canadian institutionsnot available
Fundersnot available
KeywordsPaintingESPACESpace (punctuation)Contemporary artNous
DOInot available

Abstract

fetched live from OpenAlex

Une question est posée : comment la peinture peut-elle produire une archive? Ce travail doctoral montre une volonté de poursuivre une activité picturale dans un moment où l'hybridation des pratiques définirait en priorité le champ contemporain de l'art. Développer la peinture autour du nombre, de la répétition des châssis, du visage qui échappe partiellement au mimétisme de la référence. Des enchâssements font croître la peinture dans une station à la verticale, et dans un continuum à l'horizontale. Mettre en jeu la temporalité dans la peinture, être un peintre collectionneur, être un peintre jardinier, tel est l'enjeu de mon engagement. Ce travail met en écho l'écriture et la peinture pour manifestement arriver à une forme qui tend vers la juxtaposition. Le texte est ici déterminé par une parole vivante, par un récit ténu et sériel, psychogenèse d'une histoire heurtée et d'un patrimoine iconoclaste qui induit celle d'un faire pictural. La mémoire personnelle devient une fable. Ce travail conjugue une pratique artistique personnelle avec un journal pictural aux "paroles suffoquées"155, deux entretiens d'artistes actuels : Gérard Garouste et Yan Pei Ming et la réminiscence d'une rencontre avec une artiste anglo-canadienne et membre éminente de la Slade School of Fine Art of London (UCL) : Lisa Milroy.

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)0.005
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 score0.055
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.007
Scholarly communication0.0060.005
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0550.004

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 head0.027
GPT teacher head0.235
Teacher spread0.208 · 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
Published2019
Admission routes1
Has abstractyes

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