Acousmatic Music as a Medium for Information: A case study of <i>Archipel</i>
Bibliographic record
Abstract
This article discusses the inclusion of concrete informative elements within acousmatic music, in an attempt to mix acousmatic music and sound documentary into a form of socially engaged sound art. Inspired by existing sound practices that make strong use of the sonic reality, such as soundscape composition or radiophonic art, the authors explain how they aim to address socially relevant topics within pieces where music and information are considered of equal importance. To that end, they give a detailed description of their approach through the analysis of the composition process behind Archipel (Côté and Campion 2016), a 29-minute piece focused on the access to the waterfront in the city of Montréal, Québec. Through an alloy of interviews, sound recordings gathered on the shores of Montréal and typically acousmatic sound-processing and synthesis, the piece attempts to portray the challenges and opportunities encompassed by this topic. Having found the need to go beyond the acousmatic concert format for this kind of work, the authors also briefly discuss how they are currently expanding the project to include an interactive website and a mobile application that will complement the initial concert piece.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.010 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".