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Record W2969093614

Records and Wireframes: NEON Festival, CentreSpace, Dundee Contemporary Arts, Dundee

2017· article· en· W2969093614 on OpenAlexaboutno aff
Paul Dolan

Bibliographic record

VenueNorthumbria Research Link (Northumbria University) · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionVisual artsArtOratorioArt historyMemoirSculptureTheme (computing)ArchaeologyGeographyMusicalHistoryComputer scienceWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

Wireframe Valley (remade, 2017) was selected for inclusion within a joint exhibition with Paul Walde. Wireframe Valley (remade, 2017) is a real time simulation landscape that gradually decays to reveal its wireframe basis over the duration of the exhibition. It is not video or film, but a software program created with a game engine. The duration changes depending on the length of the exhibition. In this case, it was screened for 14 days. \n \nRecords and Wireframes presents moving image works by artists Paul Dolan (UK) and Paul Walde (Canada) alongside skeletal remains of the extinct Tasmanian Tiger, on loan from the collection of the University of Dundee’s D’Arcy Thompson Zoology Museum. Curated for NEoN by artist Kelly Richardson to accompany her exhibition at DCA, ‘The Weather Makers’, ‘Records and Wireframes’ explores themes around climate change and screen culture with allusions to the past, present and future. \n \nIn the expansive video installation Requiem for a Glacier (2013), Paul Walde memorialises British Columbia’s Jumbo Glacier, or “Qat’muk”, now under immediate threat from global warming and resort development. The work shows a four-movement oratorio performed by an orchestra and chorus atop the area’s Farnham Glacier. Over thirty-seven minutes, Requiem for a Glacier features panoramic glacier views alongside the oratorio that was composed by converting data such as temperature records for the area, into musical notation. \n \nThe theme of disappearing landscapes, and data as a form of media archaeological artifact, continues in Paul Dolan’s real-time video work, Wireframe Valley (2017), which presents the gradual disappearance of a digitally constructed landscape, revealing its virtual origins. The defining features of the landscape degrade over the exact duration of the exhibition. In the context of global warming, where the physical planet is increasingly incapable of sustaining life as we know it, our refuge amongst digital environments may not placate us for long. \n \nShould we fail to alter our course, predictions for the fallout from large-scale, unchecked industry are nothing short of terrifying. Some scientists believe that a 6th mass extinction event is already underway through the “biological annihilation” of wildlife in recent decades. Recent studies suggest that the Tasmanian Tiger’s extinction in the 1930s was itself caused by drought.[1] Due to human overpopulation and overconsumption, roughly 50% of the earth’s wildlife population has been lost during our lifetime. A recently published study in the peer-reviewed journal Proceedings of the National Academy of Sciences forgoes the usual sober tone and refers to the gravity of the loss as a “frightening assault on the foundations of human civilisation”. [2] \n \nCarrying on from themes explored in Kelly Richardson’s exhibition The Weather Makers at DCA, Records and Wireframes shows the work of artists who, through their art, are creating digital records expressing how we understand our world today. These art works, like the fragmented thylacine skull, may become artifacts that future archaeologists consider in their search to appreciate how, in 2017, inhabitants of Earth understood the global environmental crisis facing them. \n \n[1] https://www.theguardian.com/science/2017/sep/28/tasmanian-tigers-on-australian-mainland-killed-off-by-drought \n \n[2] Gerardo Ceballos, Paul R. Ehrlich, and Rodolfo Dirzo (2017) ‘Biological annihilation via the ongoing sixth mass extinction signalled by vertebrate population losses and declines’ Proceedings of the National Academy of Sciences of the United States of America. See http://www.pnas.org/content/114/30/E6089 Accessed: 25/09/17.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.094
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0940.010

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 head0.214
GPT teacher head0.319
Teacher spread0.105 · 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
Published2017
Admission routes1
Has abstractyes

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