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Record W1914469256 · doi:10.7202/1031233ar

De l’iconographie : Jean-Luc Nancy et la question de l’image

2015· article· fr· W1914469256 on OpenAlexvenueno aff
Federico Ferrari, Tristan Rodriguez

Bibliographic record

VenueÉtudes françaises · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicDiverse Cultural and Historical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Cet article s’intéresse au rapport entre l’écriture et l’image, mieux : à la possibilité même d’une iconographie. Jean-Luc Nancy a, à notre époque, montré cette possibilité à l’oeuvre. C’est donc à sa pensée sur l’image qu’est consacré ce texte. Chaque penseur est une occasion de penser : il n’y a rien à « reconstruire », aucune théorie à clarifier, à expliquer ou à illustrer, mais plutôt la nécessité de réactiver une pensée, de lui rendre toutes ses potentialités inexprimées, ou seulement exprimées selon une tonalité déterminée, selon les cordes d’une voix particulière. L’oeuvre de Jean-Luc Nancy, et encore davantage la partie de son corpus dédiée à l’image, n’échappe pas à cette règle. On relira donc ses oeuvres consacrées à l’image à la lumière de la pensée iconologique de Panofsky et de l’histoire de l’art afin d’esquisser la possibilité d’une iconographie considérée comme pensée figurative et ontologie de l’image : une pratique iconographique capable de s’exposer à la question même de la pensée, de demander compte de ce que signifie penser, penser par images et à travers les images.

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: Other · Consensus signal: Other
Teacher disagreement score0.100
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.009
Scholarly communication0.0080.005
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0120.002

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 head0.041
GPT teacher head0.303
Teacher spread0.262 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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