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Record W3031777208 · doi:10.7202/1069620ar

Archéologie de l’oeuvre Net art : une esthétique du fragment

2020· article· en· W3031777208 on OpenAlexvenueno aff
Jean-Paul Fourmentraux

Bibliographic record

VenueRACAR Revue d art canadienne · 2020
Typearticle
Languageen
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionWorld Wide WebSpace (punctuation)Interface (matter)Visual artsDigital artProcess (computing)ArtSociologyInstallation artComputer scienceArt historyPerformance artThe artsVisual arts educationStudio art

Abstract

fetched live from OpenAlex

When applied to the Net, art seeks to distribute the conception of interactive systems but also to produce forms of communication and exhibition involving web surfers in the process of the artwork. Websites, home pages, online workshops, list serves, and discussion forums are the frames and territories of new forms of social interaction. On the one hand, Net artists create spaces they inhabit and enrich through the accumulation of data whose goal is to form a more or less “living” archive. On the other hand, these artists use servers, access ports, and addresses to configure a world to be experienced and lived from within, inviting web surfers to temporarily inhabit this space. By joining an aesthetic of computer codes with interface design and archival art, Net art encourages various fragments both competing and coordinated – “programs,” “interfaces,” and “images” – whose status and use I propose to redefine. In other words, through the process of distributed construction of editorial content and the interpretive practices that bring it up to date, this essay examines the systems (frameworks, interfaces) and concrete forms of this digital social interaction (contracts, rituals).

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 score0.981
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0080.020
Scholarly communication0.0140.007
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0130.002

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 head0.125
GPT teacher head0.241
Teacher spread0.116 · 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
Published2020
Admission routes1
Has abstractyes

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Same venueRACAR Revue d art canadienneSame topicCultural Insights and Digital ImpactsFrench-language works237,207