United States and Canada Transboundary Oil Spill Liability and Compensation Regimes: An Overview
Bibliographic record
Abstract
Abstract # —1141278 — In 2018, the Canadian government purchased the Trans Mountain pipeline, running from Alberta to British Columbia, along with the plans for expansion. The expansion could triple the transport capacity from 300,000 to 890,000 barrels of oil per day, and would increase the tanker traffic in the inland waterways of the Salish Sea, an area known for its sensitive marine habitat, and narrow, difficult to navigate passages. The anticipated increase in tanker traffic in this busy waterway continues to raise concerns about the impact of an oil spill and the financial means to address related injuries, particularly to natural resources. The transboundary nature of any spill further complicates the situation vis-à-vis the applicable liability regimes and response resources. Under the Canada-United States Joint Marine Contingency Plan (“JCP”), the United States Coast Guard and Canadian Coast Guard acknowledge each country's responsibility to fund their own response actions and pursue reimbursement of those costs within their respective jurisdictions. The availability of funding for a response, and to compensate injured parties, however, including the limits of liability of the responsible party, differs under each regime, and could impact the nature and scope of a response. For spills into or posing a substantial threat to the navigable waters of the United States, the Oil Pollution Act of 1990 governs and a national fund, the Oil Spill Liability Trust Fund (“OSLTF”), is immediately available to address an incident, including emergency restoration to natural resources. Canada's Marine Liability Act enables the Ship-source Oil Pollution Fund (“SOPF”) to pay claimants who have incurred damages as a result of oil pollution. Both countries' funds operate under the same principal—the polluter pays—but the compensation structure, and claims processes and procedures are entirely different. This paper provides an overview of these funding sources and claims procedures, comparing and contrasting the different systems. The discussion is meant to provide an overall understanding of potential funding pools available for spill responses under each scheme in order to facilitate transboundary spill planning and discussion.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.019 | 0.027 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".