Charting public art – a quantitative and qualitative approach to understanding sustainable social influences of art in the public realm
Bibliographic record
Abstract
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.
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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 | 0.041 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.011 | 0.026 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".