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Record W413131572 · doi:10.31165/nk.2015.81.360

A Japanese Approach to Haptic/Multimodal Art Practice and Perception

2015· article· en· W413131572 on OpenAlexfundno aff
Emilia Sosnowska

Bibliographic record

VenueNetworking Knowledge Journal of the MeCCSA Postgraduate Network · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicVisual Culture and Art Theory
Canadian institutionsnot available
FundersCanadian Institute for Advanced ResearchUniversity of MichiganHarvard University
KeywordsUnderpinningContext (archaeology)PerceptionNatural (archaeology)SociologyHaptic technologyAestheticsSpiritualityContemporary artVisual artsEpistemologyPsychologyComputer scienceArtEngineeringHistoryArtificial intelligence

Abstract

fetched live from OpenAlex

This paper reflects a fraction of research which sets out to examine the complex constructions and debates underpinning visual culture theory, and assesses its adequacy as the main theoretical framework with which to engage in contemporary interactive art. The treatment presents digital art in Japan with its roots in traditional East Asian philosophy giving the senses a prominent role in perceiving the world and enabling perfect symbiosis between humans and machines. This paper points out the expansion of this culturally and traditionally inspired spirituality from its natural and cultural context to contemporary digitally mediated environments. This is accomplished through an analysis of digital interactive work by specific artists located in Japan, such as Kumiko Kushiyama, Masaki Fujihata and Ryota Kuwakubo.

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)0.001
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 score0.010
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.009
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.055
GPT teacher head0.280
Teacher spread0.224 · 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
Published2015
Admission routes1
Has abstractyes

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