Extending Musical Form Outwards in Space and Time: Compositional strategies in sound art and audiovisual installations
Bibliographic record
Abstract
Sound and media installations are rarely considered from a time-based, formal perspective. In order to enable a greater understanding of temporal form in sound installations, I suggest a cross-disciplinary adaptation of musical form to the installation context. Due to the differences between concert and installation presentation practices – including, but not limited to, the increased agency of the mobile visitor – I re-examine form in installation contexts as the particular temporal experience co-produced by the first-person subject as they navigate in, through and out of the work’s frame. By applying this musical perspective to macro-scale formal structures, a set of tools and concepts become available for the analysis of temporal form in existing sound or audiovisual installations. Using practice-based observation and analysis, I describe several compositional strategies through which musical concepts of material and form can be extended in space and time: each of these strategies provides means with which to shape or constrain the visitor’s co-production of experiential form. Finally, I discuss several strategies that can be used for the creation of large-scale form, with particular reference to algorithmic design principles used in my recent audiovisual installation, Room Dynamics.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.025 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".