Indigenous self-determination in fisheries governance: implications from New Zealand and Atlantic Canada
Bibliographic record
Abstract
The United Nations’ Declaration on the Rights of Indigenous Peoples (UNDRIP) recognized Indigenous rights to self-determination. How these rights can be realized in territories governed by settler-states remains unclear. For fisheries, the need to understand processes that support Indigenous self-determination has gained urgency due to government commitments and investor interest in developing ocean and coastal resources, or Blue Economies, amid rapid climatic changes. Here, we explored Indigenous groups’ fishery development experiences following two approaches to reconciling Indigenous fishing rights. In New Zealand, we examined Māori groups’ experiences following the 1992 Treaty of Waitangi (Fisheries Claims) Settlement Act. The Settlement granted Māori iwi (tribes) rights to self-govern non-commercial harvests, restrict fishing pressure in state-approved customary fishing areas, and participate in state-run systems for commercial fisheries management. In Canada, we investigated Indigenous fishery development initiatives following the Supreme Court of Canada’s 1999 ruling R. v. Marshall . Marshall reaffirmed Treaty-protected rights to harvest and trade fish, held by Mi’kmaq, Wolastoqey, and Peskotomuhkati Peoples, to support a “moderate livelihood.” We document how, in both cases, Indigenous groups’ self-determination remains constrained by actions from state regulatory and enforcement agencies that govern market access, other resource users’ activities, and processes for collecting and sharing information about fish populations. Indigenous groups’ experiences highlight that: 1) reallocations of harvest rights, on their own, are an insufficient means to redistribute access to benefits from fisheries; 2) the constraints Indigenous families have experienced in their attempts to develop small-scale fishing operations correspond to settler-state policies and cannot be addressed solely through changes to Indigenous leaders’ management decisions; and 3) polycentricity in governance regimes can pose problems for Indigenous self-determination, when citizens with political authority resist efforts to support Indigenous fisheries. To address these challenges, we call for legal reforms that require settler-state governments to support Indigenous self-determination, to overcome the political risks politicians face when advocating for a non-majority group’s interests.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.023 | 0.010 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".