Bibliographic record
Abstract
Recognizing processes of sonic marginalization, contemporary sound scholars increasingly orient their work towards an awareness of historical contexts and theoretical frameworks that emphasize diversity, intercultural understandings, and the multiple intersecting relationships of power in sound studies, media studies, and related areas. As evidenced in recent calls to remap and decolonize the field through alternative listening approaches – such as “fugitive listening” (Brooks 2020), “border listening” (Cárdenas 2020), “critical listening positionality” (Robinson 2020), and “abolitionary listening” (Arthur et. al. 2021) – it is imperative to consider the ways in which listening heals as well as harms, attunes as well as captures, thereby requiring substantial critical and creative inquiry. Using a case study approach, auto-ethnography, and interviews, this paper turns to a multi-media exhibition at Gallery TPW in Toronto to examine divergent, collective, and alternative listening practices that open up other worlds already out there by attuning to forgotten histories and aural experimentations, forging what I can “otherwise social relations” through intimate encounters with sound and its wider historical and political entanglements. Curated by Toleen Touq, the exhibition Another World That Sounds Like You (2023) features sound-based works by artists Bani Abidi, Nick Dourado, JJJJJerome Ellis, Urok Shirhan, and Hong-Kai Wang. This multi-faceted show centres the relationship of sound to various global social, political, and cultural movements, and invites audiences to participate in an act of slow, careful, communal engagement within a space designed to resemble a living room with several rugs and low comfortable seating, nurturing warm and participatory forms of connection. The listening practices and affective experiences that the exhibition stages are established through a confluence of mechanisms – the material affordances and implications embedded within the installation design, which are tied to the show's conceptualization, and the selection of an international range of artworks that endeavors to cross boundaries and borders. When taken together, as in the case in Another World That Sounds Like You, these components enlist the visitor in a web of relations that is equal parts complex, meditative, and shared. I ultimately argue that the sonic, when distributed across otherwise relational modes, enunciates alternative enactments of sociality and collectivity through methods of intimacy, opacity, and fugitivity.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.244 | 0.059 |
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".