Bibliographic record
Abstract
Max Ritts’s A Resonant Ecology is an analytically incisive and theoretically innovative contribution to environmental humanities, sound studies, and political ecology. Informed by years of research on British Columbia’s North Coast, Ritts draws on a diverse set of case studies, interviews, and extensive listening—from hydrophone monitoring to musical performances to everyday coastal soundscapes—to explore how sound is shaped by and reveals the intertwined dynamics of ecological crisis, capitalist development, and settler colonialism. The book’s analysis of the political ecology of sound on the North Coast is marked by a keen attentiveness to the fissures and tensions that emerge when sound is mobilized to produce knowledge, assert truth claims, and shape environmental sensibilities. At the core of A Resonant Ecology is an argument for a sonic materialism that treats sound not as a raw truth of nature but as a thoroughly mediated object and a site of social and political negotiation. Ritts develops this argument through an analysis of sonic practices, discourses, and infrastructures—an analysis that is deeply interwoven with the book’s vivid storytelling and first-person vignettes. These narrative strategies both illuminate and enact his claim that sound is a key modality through which states, industrial actors, and communities negotiate relations to place, power, and knowledge under late capitalism.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.048 | 0.033 |
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".