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Record W2047223885 · doi:10.1177/1354856509105112

Self-Emulation

2009· article· en· W2047223885 on OpenAlexaff
Caroline Seck Langill

Bibliographic record

VenueConvergence The International Journal of Research into New Media Technologies · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsNarrativeExhibitionDilemmaActive listeningEmulationNew mediaSociologyVisual artsElectronic mediaMedia artsWhite (mutation)Order (exchange)AestheticsMedia studiesArtMultimediaComputer sciencePsychologyLiteratureWorld Wide WebEpistemologyCommunicationBusiness

Abstract

fetched live from OpenAlex

/ In this article I examine the ways the archival process has compelled artists working in early electronic media, and new media to `self-emulate', to produce new versions of their artworks. I propose that upgrading steals the narrative of progress that spoke to the cultural effects of emerging technologies informing the original production of the work. Three artworks are examined in order to investigate how self-emulation has effected the evolution of new media artworks: The Helpless Robot by Norman White (1986—2004), Small Artist Pushing Technology (1987—) by Doug Back, and Listening Post (2003—) by Mark Hansen and Ben Rubin. The production of new versions of electronic media works primarily concerns integration with contemporary modes of exhibition and aesthetic trends. However, the materials that generated early electronic media works spoke to the larger discourse of our relationship to technology. This article investigates this dilemma.

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)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.011
Scholarly communication0.0060.007
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.003

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 head0.115
GPT teacher head0.391
Teacher spread0.276 · 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

Citations2
Published2009
Admission routes1
Has abstractyes

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