To Cooperate or Not? Why Working Together is Essential in the Arctic
Bibliographic record
Abstract
Abstract The Norwegian Arctic covers Svalbard, Bear Island, Jan Mayen and the Barents Sea. 80% of all shipping activities in the Arctic are within Norwegian territorial waters and the Exclusive Economic Zone. To reduce the risk for accidents, the Norwegian authorities have established several preventive measures. Among these are ship reporting systems, traffic separation schemes in international waters and surveillance capabilities. If an accident has occurred and an oil spill response operation must be organized - resources, equipment, vessels and manpower from Norwegian and neighboring states will be mobilized. In 2015, the Norwegian Coastal Administration finalized an environmental risk-based emergency response analysis for shipping incidents in the Svalbard, Bear Island and Jan Mayen area. This scenario-based analysis has resulted in a number of recommendations that are currently being implemented to be better prepared for oil spill response operations in the Norwegian Arctic. Further, a large national oil spill response exercise in 2016 was based on one of these scenarios involving at sea and onshore oil spill response at Svalbard. The 2016 exercise, working within the framework of the Agreement on Cooperation on Marine Oil Pollution Preparedness and Response in the Arctic between Canada, Denmark, Finland, Iceland, Norway, Russia, Sweden and the USA (Arctic Council 2013), focused on a shipping incident in the Norwegian waters in the Barents Sea, close to the Russian border. Every year, as part of the Russian – Norwegian Oil Spill Response Agreement and the SAR Agreement in the Barents Sea, combined SAR and oil spill response exercises are organized. These are held every second year in Russia and every second year in Norway. There is an expected increased traffic and possible increased risk for accidents in the Arctic waters. In order to build and maintain an emergency response system to this, cooperation between states, communities, private companies and other stakeholders is essential. It is important that all actors that operate and have a role in the Arctic are prepared and able to help ensure the best possible emergency response plans. We depend on one another, this paper highlights some of the ongoing activities designed to strengthen the overall response capabilities in the Arctic.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".