Ombra Musici II: Classical Music Performance and Public Space
Bibliographic record
Abstract
Ombra Musici II presents a video projection of a violinist performing solo classical works on a screen installed on a rooftop terrace adjacent a major street and public plaza in Portland, Oregon during the Portland Winter Light Festival 2023. An accompanying research project asked: How do outdoor digital installations of classical music performance impact people's feelings about classical music performance? How do outdoor digital installations of classical music performance impact people's feelings about the urban environment after dark? Employing contextual observation and semi-structured interviews with a total of 117 attendees, and building on and evaluating theories of observing media audiences in urban contexts, placemaking (digital, creative, and mobile), and expanded cinema (namely montage and dispositif), the research found that group size and dynamics had a strong effect on the length of engagement with the work, that most participants used their digital devices to capture and share the experience outside of the site, that sound was crucial in creating a communal and comfortable space, as well as expanding the footprint of the performance, and that classical music in particular helped to challenge the narrative expectations of this particular public space, deepening people's connection to one another in the space. The findings may be useful for shaping both the design of digital and creative placemaking initiatives, as well as further experimentation with the presentation of classical music performance in public space.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".