Smart oceans governance: Reconfiguring capitalist, colonial, and environmental relations
Bibliographic record
Abstract
Abstract How does the digitisation of the ocean reconfigure capitalist, colonial, and environmental relations? What analytic tools allow us to trace their intersecting dynamics? These are the central questions that we take up through an examination of smart oceans governance along the west coast of Canada, where the state is developing new institutional partnerships to manage the expansion of fossil fuel infrastructure across unceded Indigenous lands and waters. In this context, laden with environmental risks and resurgent anti‐colonial politics, state actors are implicating smart oceans governance in efforts to harmonise capitalist growth with sustainability mandates and the ‘recognition’ of Indigenous self‐determination. Our analysis draws on environmental state theory, critical indigenous studies, and human geographies of the ocean, to analyse interviews, Access to Information requests, scientific studies, and policy reports. Our findings suggest that smart oceans governance poses novel risks to Indigenous peoples and their distinctive ‘seascape epistemologies’. At the same time, we observe in this medium new limits to the state's ability to consolidate settler colonial authority and extend possessive colonial entitlements to Indigenous lands and waters. First Nations are also engaging with smart oceans governance in ways that assert ‘Indigenous data sovereignty’, help chart their own political and territorial ambitions, and carve out meaningful spaces of Indigenous marine stewardship.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".