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Record W2758673927 · doi:10.1386/aps.2.1-3.87_1

Planning a suburban public artscape: The case of Mississauga, Canada

2012· article· en· W2758673927 on OpenAlexaffabout
Alison L. Bain, Zainub Verjee

Bibliographic record

VenueArt & the Public Sphere · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsYork University
Fundersnot available
KeywordsSculptureRealmPublic artPoliticsBeijingCultural geographyWork (physics)Political sciencePublic administrationSociologyGeographyChinaVisual artsArtArchaeologySocial scienceHuman geographyEngineeringLaw

Abstract

fetched live from OpenAlex

Abstract This article critically examines the cultural planning and policy frameworks recently developed in the suburban municipality of Mississauga, now considered Canada’s sixth largest city, to ameliorate an impoverished public artscape. In the absence of a public art programme and a three-decades-long anti-art mayoral regime, Mississauga’s public artscape has emerged in an ad hoc manner with no rationale for the distribution of art within the city and no strategy for engaging and empowering diverse publics. An analysis of Mississauga’s first Culture Master Plan (2009) reveals that public art is treated as a straightforward mechanism for animating the public realm despite the lived suburban realities of significant spatial distances, high car dependence, nine-to-five commuting patterns, low foot traffic and enormous cultural diversity. A critique of the ensuing Framework for a Public Art Program (2010) report produced by the Culture Division is used to evaluate the most recent addition to Mississauga’s public art collection, the sculpture Buen Amigo (2011) by Chilean artist Francisco Gazitua. The sculpture was privately commissioned by the developers of the Absolute World luxury condominium 56-storey towers by Beijing architect Yansong Ma. The towers and the sculpture are intended to be landmarks that help to brand the suburban municipality as culturally sophisticated and economically dynamic. This article considers the spatial politics and interrelationships between the different urban actors involved in the selection of one work of public art and critically assesses the cultural policy frameworks that informed this decision-making process.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.065
GPT teacher head0.279
Teacher spread0.214 · 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 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

Citations1
Published2012
Admission routes2
Has abstractyes

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