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Record W4322628522 · doi:10.1386/eta_00117_1

Analysing eco-art installations for their value in affecting change

2023· article· en· W4322628522 on OpenAlexfundno aff
Carmela Cucuzzella

Bibliographic record

VenueInternational Journal of Education through Art · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Philosophy and Ethics
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRealmAnthropoceneAnthropocentrismAction (physics)Value (mathematics)PoliticsSpace (punctuation)Environmental ethicsPublic spacePublic artSociologyEngineering ethicsAestheticsEnvironmental planningPolitical scienceArchitectural engineeringEngineeringGeographyComputer scienceVisual artsArtLaw

Abstract

fetched live from OpenAlex

A distinctive form of environmentally driven art and design practice has emerged in urban contexts over the last few decades. This practice has developed a unique discourse aiming to inform and rally the public to action. The global eco-didactic direction of this artwork not only demonstrates an alignment with pressing ecological issues but is driven by an urgent need to explain unsustainable anthropocentric practices. Adopting the public realm as an audience is key for these works, since this enables human encounters with the issues collectively, contributing to the potential of ‘public space as a political forum’. This article poses the question ‘are these works a means of revealing the Anthropocene?’ A series of art and design installations are examined along with a discussion of the what these works aim to accomplish and how this can be achieved.

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)0.003
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 score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0060.014
Scholarly communication0.0090.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.073
GPT teacher head0.351
Teacher spread0.278 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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