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Record W2756595302 · doi:10.1386/aps.2.1-3.9_1

Charting public art – a quantitative and qualitative approach to understanding sustainable social influences of art in the public realm

2012· article· en· W2756595302 on OpenAlexaffabout
Cameron Cartiere

Bibliographic record

VenueArt & the Public Sphere · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Spaces through Art
Canadian institutionsEmily Carr University of Art and Design
Fundersnot available
KeywordsRealmCornerstoneArgument (complex analysis)Political scienceSustainable developmentDisciplineUrban designSociologyPublic relationsUrban planningEnvironmental ethicsSocial scienceGeographyEngineeringLawCivil engineering

Abstract

fetched live from OpenAlex

Abstract As public art continues to serve as a cultural cornerstone in the regeneration strategies of urban areas across North America and the European Union, the need for quantitative data on the sustainable economic, environmental and social impacts to support the beneficial claims of art in the public realm is becoming increasingly imperative. While much has been written to explore the development and expansion of public art, particularly as an agent of urban change, little by way of substantive evidence exists to support the anecdotal evidence and qualitative observations that underlie the argument of public art as a sustainable vehicle for urban regeneration and social change. This article explores some of the assumptions regarding the long-term effects of public art in the urban environment and outlines the development of a multi-disciplinary project in Vancouver, British Columbia that is endeavouring to develop a series of socially engaged public art projects to lay the foundation for research that aims to garner valuable qualitative and quantitative data reflecting the influences of public art within Canadian urban society.

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 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)0.015
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.798
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0020.002
Scholarly communication0.0010.004
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.180
GPT teacher head0.396
Teacher spread0.216 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations4
Published2012
Admission routes2
Has abstractyes

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