Transboundary Indigenous Oil Spill Risk and Eco-cultural Resources
Bibliographic record
Abstract
The Strait of Juan de Fuca experiences high oil spill risk due to dense vessel traffic in the region. An oil spill in the region would cross the Canada-U.S. border, affecting Tribes, First Nations, states, and provinces. Due to the relative remoteness of these areas, Tribes and First Nations may be the first on the scene in the event of an incident. However, regulatory differences associated with the Canada-U.S. border and federal planning and response structures that were not built with indigenous governments in mind can impact effective prevention, preparedness, and response to oil spills, with particular consequences for Indigenous communities and culturally significant resources. To build capacity across borders and support collaboration among Tribes and First Nations in marine resource stewardship and oil pollution prevention, the Makah Tribal Council and Office of Marine Affairs, with participation from Nuu-Chah-Nuulth Tribes, hosted a virtual workshop on Indigenous oil spill risk and eco-cultural resources. The objectives of the workshop were to create connections among Tribes and First Nations, share information and experience, and identify opportunities to leverage past successes and build new collaborations. Key messages emerged from two days of discussions, including 1) cultural protocols can be used to build foundational relationships for collaboration, 2) watershed moments can arrive through meaningful collaboration, not only after crises, and 3) cross-pollination and partnership have advanced the ability of some Tribes and First Nations to prepare for and respond to spills. Additionally, an artist captured key elements of the discussions in graphic recordings, which added a rich layer of visual storytelling that helped to address some of the shortfalls of virtual meetings. In our presentation, we will share key takeaways from the workshop and identify potential next steps in building transboundary relationships for oil spill prevention, preparedness, and response.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".