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Record W2560583557 · doi:10.7202/1038075ar

Par-delà le naturalisme : médiatisation du sublime dans les oeuvres d’Olafur Eliasson et Ryoji Ikeda

2016· article· en· W2560583557 on OpenAlexvenueno aff
Maryse Ouellet

Bibliographic record

VenueRACAR Revue d art canadienne · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSublimeNaturalismRepresentation (politics)Subject (documents)Interpretation (philosophy)ArtRelation (database)Art historyHumanitiesPhilosophyEpistemologyComputer science

Abstract

fetched live from OpenAlex

Although the sublime is commonly associated with nature, the historical determinants of this relation are frequently ignored. Art historians and curators who attempt to define a contemporary sublime often anachronistically link recent artworks with modern categories marked by a now contested representation of the world. Such is the case of the “natural sublime,” which emerged around the turn of the eighteenth century and exemplifies what Philippe Descola describes as a “naturalistic” cosmology characterized by a separation between Nature and Culture. Starting from a case study of two recent art installations associated with the sublime, namely The weather project (2003) by Olafur Eliasson and the series systematics and datamatics (2012) by Ryoji Ikeda, this article examines how these works reconfigure the relation between the subject and the world, in order to characterize the contemporaneity of their representation of the sublime. It suggests that these installations help reformulate our interpretation of it by emphasizing the power of technological and digital mediations to connect the human and the non-human worlds.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.022
Scholarly communication0.0100.008
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.019
GPT teacher head0.184
Teacher spread0.165 · 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 designTheoretical or conceptual
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
Published2016
Admission routes1
Has abstractyes

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