Bibliographic record
Abstract
Canadian artist, composer, and musician Jesse Stewart examines the implications of the famous dictum, “Music is liquid architecture; Architecture is frozen music.” How do—or might—the fields of music and architecture illuminate one another? What is gained when we bring insights, approaches, and methodologies associated with architecture to bear on music creation and vice versa? This chapter explores these questions through an examination of several points of intersection intersections between music and architecture, including the work of composer architect Iannis Xenakis (1922–2001); contemporary architects Santiago Calatrava and Steven Holl; three of Stewart’s mentors: composer and music theorist James Tenney (1934–2006), composer and accordionist Pauline Oliveros (1932–2016), and composer and baritone saxophonist David Mott; as well as Stewart’s own interdisciplinary creative practice. In the second part of this text, Stewart engages in a dialogue with Federica Goffi and Isabel Potworowski. Together, they instructed an (un)common workshop on music and architecture at Carleton University in which first-year architecture students created ambiguous representations that can be described as drawing-scores. Such pieces lean towards the abstract nature of musical graphic scores while maintaining spatial elements, such as conventional architectural representation including plans or sections.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".