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Record W4400777014 · doi:10.1386/vcr_00079_1

Vera Frenkel’s String Games: Improvisations for Inter-City Video

2023· article· en· W4400777014 on OpenAlexaffabout
Mikhel Proulx

Bibliographic record

VenueVirtual Creativity · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicArts, Culture, and Music Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsString (physics)Computer scienceArtTheoretical physicsPhysics

Abstract

fetched live from OpenAlex

In the autumn of 1974, the Canadian artist Vera Frenkel staged String Games: Improvisations for Inter-City Video . Two groups of participants – five each in Toronto and Montreal – engaged in a remote version of the classic string game cat’s cradle . String Games is the first piece of telematic art. However, art historical attention to the artwork has been insufficient. String Games emerged from a watershed moment for network technologies, specifically within a context of telecommunications development in the Canadian nation state. Telecommunications-based art has a long legacy in Canada, the country that exactly a century before Frenkel’s artwork saw Alexander Graham Bell’s patent for the telephone in 1874. His namesake company launched the Bell Canada Conference TV System in the early 1970s. In its day, the System was one of only four organizations worldwide that provided conferencing technology that engaged video, audio and computer networks. Decades before studies alerted us to the cognitive overload of Zoom fatigue, the effects of ‘continuous partial attention’ and to the importance of non-verbal, bodily signals in digital media, Frenkel and her collaborators used telematics to consider new ways of being together with and through embodying new communications tools. This article provides a historical analysis of String Games , situates its role within the history of networked art, and explores the artwork’s co-operative realization of live connection and a feeling of co-presence in the context of technological development in the Canadian nation state. Within the context of early interactive video work, String Games was a notable innovator.

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)0.004
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 score0.166
Threshold uncertainty score0.330

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0110.008
Scholarly communication0.0070.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.002

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 head0.082
GPT teacher head0.358
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

Citations0
Published2023
Admission routes2
Has abstractyes

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