Audible developments : geographies of capitalism, nature, and sound on BC's North Coast
Bibliographic record
Abstract
Proceeding from Denning's (2015) claim that sound is fundamental to social and political analysis, and hence, constitutive of 'audiopolitics', the dissertation argues for sound as an expressive medium of industrial development politics on the North Coast of British Columbia (BC), 2007-2015. Informed by sound studies, political ecology, and critical ethnography (Hart 2006), and drawing on eighteen-months of fieldwork (2012-2015), the dissertation identifies connections between large-scale development forces and communities experiencing uneven change. Chapter 2 engages environmental conservation activities through acoustically-mediated whale research, finding that situated conceptions of 'nature experience,' linked to institutionally sanctioned practices of interspecies listening, hold formal consistencies with Adorno's (1951) culture industry. Chapter 3 proceeds as a comparative study of noise abatement in the restructuring city of Prince Rupert, and follows three community campaigns which entangled themselves in locally-operative forms of neoliberal eco-governance. It argues that collective expressions of left melancholy (Brown 1999), and the reified conception of situated 'past-ness' they articulate, emerged from efforts to contest industrial sounds without challenging the logics they relied upon. Chapter 4 considers techno-scientific efforts to chart the biological impacts of ocean noise, now considered an emergent marine hazard linked to cavitating ship propellers. The chapter understands the consensus around the regional management of ocean noise 'risk' as evidence of hegemonization (Gramsci 2011), revealing a correspondence between marine bio-acoustics practices and capitalist efforts to attain sustainable growth trajectories in 'risky' marine space. Chapter 5 examines Gyibaaw (2006-2012), a musical project founded by two teenagers from the Gitga'at First Nation. Using Hall's (2017) concepts of articulation and conjuncture, it presents Gyibaaw as decolonial audiopolitics, and insists upon the significance of 'Indigenous black metal' at a contemporary nexus of Indigenous resurgence, resource extractivism, and ascendant white ethno-nationalism. Across these cases, sounds materialize as potent yet uncertain objects of social mediation, with their political valence not known in advance. The dissertation consistently observes deepening conditions of technological mediation, co-productive of new sonic natures and capitalist social forms, with consequences for local capacities to negotiate socio-ecological change and chart progressive futures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".