Composing Situation: An approach for understanding and repeating a musical practice
Bibliographic record
Abstract
This paper is about finding relationships within my own composition process, how these relate to my relationships with the world around me, and how these impact the music that I make. In this paper I will touch on how my work has been influenced by psychogeography, making music about locations, and my experiences working in community arts. I will discuss my influences from the work Situationists International and later psychogeographic explorations, the community art world in Toronto, discussing how they have influenced my composition process and how the relationships between people, places, and sound play into the music that I compose, and the musical worldviews that helped me shape these influences into my own work. I will further explore, specifically, a part of my process which involves the setting up of situations in which music occurs as part of my compositional practice, discussing how the situation in which music is being made impacts that music, and how the music can impact the situation, finding reciprocity within these musical relationships. keywords: psychogeography, composition, Situationists
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.017 | 0.055 |
| Scholarly communication | 0.020 | 0.021 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".