Aquaculture’s offshore frontier: learning from the Canadian courts on ocean grabbing, ocean privatization, and property as process
Bibliographic record
Abstract
Abstract Many coastal nations have endorsed the Blue Economy as both an economic and environmental opportunity, despite numerous questions as to how industrial expansion into deep ocean waters might be regulated for sustainability. Aquaculture is one industry actively promoting a move offshore, with numerous offshore leases in development. Drawing on the history of aquaculture in the nearshore, and relying on a processual approach to property, we explore questions around the regulation of privatized ocean spaces: What can court cases involving aquaculture in the nearshore tell us about the role of law in promoting sustainable offshore ocean spaces? And what in turn does this suggest about extractive capitalism, the privatization of ocean spaces, and the law? We examine 46 Canadian court cases which cover a 30-year time frame and multiple Canadian jurisdictions. We argue that there are lessons here regarding the questionable ability of law to effectively regulate existing or future aquaculture operations once privatization emerges. The lessons from these Canadian court cases, taken together with a burgeoning literature on legal geography, more-than-human methodologies, and critical environmental law, suggest the varied legal dimensions of deep-sea aquaculture frontier imaginaries and highlight the real limits to regulating the extraction of resources in this perceived open space (terra nullius). We highlight crucial barriers to sustainability through what we are calling jurisdictional opaqueness in regulatory issues. The results include poor regulation and overlapping or contested jurisdictions, which relates in turn to inadequate consultation, frequent environmental problems (toxic chemicals, anoxia, salmon escapes, marine debris), and scientific disputes.
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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 | 0.012 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.038 | 0.031 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".