Planning a suburban public artscape: The case of Mississauga, Canada
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.051 | 0.008 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".