Institutional navigation of oceans governance: Lessons from Russia and the United States Indigenous multi-level whaling governance in the Arctic
Bibliographic record
Abstract
Oceans governance occurs through overlapping, multi-level institutions that often fail to recognize Indigenous sovereignty and self-determination. The International Whaling Commission (IWC) provides pathways for recognizing Indigenous rights. However, observed power asymmetries and cross-level local to international conflicts threatened subsistence rights and generated research and advocacy fatigue for Chukchi, Iñupiat, Saint Lawrence Island Yupik, and Siberian Yupik communities in the USA and Russia. We conduct an institutional analysis of Indigenous bowhead whaling governance based upon lived experiences of Indigenous authors, primary documents from co-management organizations, national agencies, the IWC, and extant literature. We explore how Indigenous co-management organizations increased sovereignty and self-determination for communities whose culture, identities, livelihoods, and origins are intimately connected to marine mammal hunting. Our study also provides lessons for the United Nations Decade for Ocean Science on the challenges of institutional navigation and the role of embodied resurgent practice amongst Indigenous communities within Earth system governance.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".