<i>RADAR</i>: Challenging Colonial Soundscapes and Violence through Creation and Performance
Bibliographic record
Abstract
In this article, Spy Dénommé-Welch and Catherine Magowan examine how sound is used in the chamber work RADAR to create a visceral experience for the audience and musicians that addresses themes of violence, grief, and the effects of colonialism. The authors reflect on the historical and contemporary implications of music, including music in alternative and experimental spaces, and how traditional spaces are often inaccessible to racialized and/or marginalized musicians. Within this landscape, the authors examine how RADAR works to disrupt Eurocentric conventions of music and performance while responding to Canada’s role in the perpetuation of violence against Indigenous women, girls, and Two-Spirit peoples. In addition, Dénommé-Welch and Magowan share their collaborative process and articulate their rationales for RADAR’s structure and unconventional soundscape. Finally, the authors reflect on the rehearsal process leading up to the premiere of RADAR and how intercultural, decolonizing approaches are important strategies for engaging with musicians and making space for more inclusive artistic practices.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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".