Research and creation: Socially-engaged art in The City of Richgate Project
Bibliographic record
Abstract
Combining research and art in the public sphere can have an enormous impact on urban societies. In places like Richmond, British Columbia, Canada, where over the past decades globalization has radically altered the social landscape, new approaches to public art and modes of representation can begin to reflect complex individual everyday experiences in a way that census statistics and traditional public monuments cannot. In this article, The City of Richgate , a four-year research/creation project funded by a pilot programme for the Social Sciences and Humanities Research Council of Canada, will be described and discussed in relation to contemporary art criticism and discourse. Specifically, debates between critics Claire Bishop and Grant Kester will be used to reflect on Richgate , and how aesthetics play a part in socially-engaged public art projects such as this one.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.036 | 0.043 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.003 | 0.035 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".