Putting the Public in Public Art: An Ethnographic Approach to Two Temporary Art Installations
Bibliographic record
Abstract
Abstract Temporary public art installations are an increasingly common sight in industrialized cities. This reflects local government and civic organizations’ interest in the potential social and economic benefits of art, as well as artists and curators’ interest in engaging “the public.” Yet little systematic social‐scientific attention is paid to the ways that public art, once installed, affects its site, and the ways that people interact with it. How can these artworks be understood as “public”? What kinds of urban publics do they produce? Approaching these questions as an urban anthropologist, I analyze ethnographic material from two pieces. One of these pieces was Kim Morgan's 2006 work Time Transit, a mixed‐media installation on an operational city bus in Regina, Saskatchewan, which invited passengers to co‐produce the art via text messages. The other piece was Situated Cinema–created by Tom Evans, Craig Rodmore, and Will Vachon in 2012–a demountable micro‐cinema that moved to different sites in Winnipeg, Manitoba, projecting short experimental films about cities. Analysis of the 3,960 text messages sent during Time Transit and interviews and observations conducted at Situated Cinema shows that each installation intervened in the socio‐spatial dialectic of its sites in original and sometimes unanticipated ways. Moreover, each produced and mediated public dialogue in a distinct sense and to different degrees. I conclude by reflecting on what an ethnographic approach can reveal about the publicness of public art—and what it might leave out.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.020 | 0.022 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".