The political difference of public art: exploring contested murals in Vancouver’s Chinatown
Bibliographic record
Abstract
This article outlines the political underpinnings of public art in historically marginalized neighbourhoods. It challenges celebratory and ‘positive’ notions of public art towards a more conflict-attuned conceptualization of the manifold tensions within public art. It proposes the conceptual framework of the political difference of public art to study the multiplicity of conflicts emerging around the production of art in public space, for example, between policymakers and artists. By interconnecting political theories of conflict with public art, the article discusses the empirical case of downtown Chinatown in Vancouver, BC, Canada, and four commissioned artworks placed in its public realm in 2019. The politics of public art revolve around the administrative goals and management practices that govern public art, aiming to produce consensus, cohesion and order. The political of public art, by contrast, inscribes itself into urban space via unregulated creative articulations. This article unpacks the implicit and explicit differences between artists, policymakers, planners and community organizers, and offers a unique conflict-theoretical framework for public art. This conceptual framework helps to nuance an understanding of both public art and public space as contested within conflict-laden urban politics of belonging, inclusion and identity.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".