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Record W2613765832 · doi:10.7202/1048837ar

Il ne suffit que de regarder

2017· article· fr· W2613765832 on OpenAlexvenueaboutno aff
William Delisle

Bibliographic record

VenueSens public · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

En raison de la tournée de Georges Didi-Huberman et de l’exposition Soulèvement, présentée par le Jeu de Paume, à travers le monde (Paris, Barcelone, Buenos Aires, México et Montréal), cet article fait un retour sur un ouvrage marquant du philosophe et historien de l’art français, Images malgré tout (2003, Éditions de Minuit). Dans un monde constamment submergé d’images, de représentations, comment pouvons-nous interpréter les images d’Auschwitz ? Sont-elles encore regardables ou demandent-elles trop d’engagement émotionnel ou intellectuel de celui ou celle qui les regarde ? Comment nous plaçons-nous dans l’imagerie de l’horreur ? Cet article propose un ajointement entre les pistes conceptuelles et éthiques de l’image que Georges Didi-Huberman propose dans son essai et les éléments élaborés par Sigmund Freud sur le désir et la pulsion scopique ainsi que ceux élaborés par Jacques Lacan sur le regard. À travers les exemples de Georges Didi-Huberman et l’apport de la psychanalyse, cet article laisse la place à une proposition éthique que l’on obtient grâce au compromis des multiples éléments qui composent l’image (ontologie, esthétisme, technique) et du regard, de son domaine subjectif et unique ; une éthique du malgré tout, du risque, basée sur les moyens de percer le réel, ce terrible réel des camps de concentration, de la machine-à-mort qu’était Auschwitz.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.027
Scholarly communication0.0080.011
Open science0.0010.005
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0110.004

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 head0.077
GPT teacher head0.297
Teacher spread0.220 · 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
Published2017
Admission routes2
Has abstractyes

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