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Record W2183639342 · doi:10.1080/14626268.2015.998683

Digital eco-art: transformative possibilities

2015· article· en· W2183639342 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDigital Creativity · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsTransformative learningContemplationDigital artWitnessDigital mediaSociologyNew mediaAgency (philosophy)Visual artsAestheticsArtComputer scienceSocial scienceWorld Wide WebEpistemology

Abstract

fetched live from OpenAlex

Cave paintings bear witness that, early in human cultural development, art and the means to create it (technology) became a method of expression and translation of human interconnectedness with nature defined as the non-human-made world. Contemporary new media artists interacting with nature through the medium of digital technologies in situ continue this exploration within the genre referred to as “digital eco-art”. LocoMotoArt, an independently powered creative field system, was used as a vehicle for conducting media arts practice in natural settings during a three-year qualitative field research project. Findings indicate that human–technology–nature interconnectedness is a possible conduit for establishing a role for digital technology beyond social networking, computing, information gathering and gaming to engage with nature. We argue that digital eco-artists are at the vanguard of creating a new sense of aesthetic and environmental engagement, proportions of which emerge as transformative possibilities. The art experience of digital eco-art can change from being a contemplative one to a living experience.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.614
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.005

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 head0.025
GPT teacher head0.253
Teacher spread0.228 · 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