Sounding Out Normative and Colour-Blind Listening in Acoustic Ecology
Bibliographic record
Abstract
Background: The field of acoustic ecology emerged from Simon Fraser University in the late 1960s during which time R. Murray Schafer and the World Soundscape Project studied everyday soundscapes and the rise of urban noise. While it was an innovative approach to understanding the relationship between humans and their environments, it reproduced the dominant frameworks of this period. Analysis: This article argues that contemporary acoustic ecology discourse continues to frame noise, silence, and urban acoustic design through a white normative and colour-blind listening framework. This article examines dominant authorship and citation practices within leading journals that publish soundscape literature as well as sound mapping practices. Conclusion: After also surveying seldom-cited soundscape research that interrogates the environmental listening and sound-making practices of BIPOC and marginalized communities, the article concludes that there is a need for contemporary soundscape research to incorporate more intersectional and decolonial modes of environmental listening.
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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 | 0.018 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.009 | 0.065 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".