CANADA-UNITED STATES-DIXON ENTRANCE (CANUSDIX) EXERCISE A MODEL OF INTERNATIONAL COOPERATION FOR PLANNING AND PREPAREDNESS
Bibliographic record
Abstract
ABSTRACT Since 1992, the Canadian and U.S. Coast Guard, Province of British Columbia, State of Alaska, OSRO'S, and several other organizations and authorities have joined together in a unique annual exercise program held near Dixon Entrance, a remote waterway marking the U.S./Canadian border at the southern tip of the Alaskan panhandle. Following a continuous improvement philosophy, a growing number of participants from both nations have made great strides in improving preparedness and response at the trans-boundary. Conducted over a 4 day period, CANUSDIX is an innovative combination of spill scenarios, training workshops, equipment deployment, and coordinated multi-year planning. Unlike conventional exercises, CANUSDIX is a year-round program with continuous effort directed toward achieving goals outlined in a formal 2-year workplan. Multi-year efforts include communications and logistics planning and evaluation of web-based information sharing systems. Canadian and U.S. OSRO'S also conduct a periodic review of equipment inventories and jointly plan future capital purchases to ensure equipment compatibility and avoid redundancy. Coordinated planning and exercising by partner agencies is a necessity for Dixon Entrance, an extremely remote, environmentally sensitive, region with severe weather, limited infrastructure, and a sparse road system. Resource trustees on both sides of the border are also key participants, due to crucial subsistence fisheries and numerous historical resources such as culturally important archeological sites. Innovation is a hallmark of CANUSDIX. For example, logistics skills were robustly tested by the “logistics board game,” debuted at CANUSDIX 2003 in Prince Rupert, BC. Resembling sophisticated tabletop war games, the board game employs tokens representing different types of oil spill cleanup equipment and personnel. Tokens are deployed on a board based on a chart of the response area. The logistics game required players to confront realistic equipment mobilization time constraints, while simulating the uncertainties associated with all spill responses. Other significant milestones of CANUSDIX include publication of Geographic and Wildlife Response Guideline Annexes to the Canada-United States Joint Marine Pollution Contingency Plan, a landmark bi-lateral planning, preparedness and response agreement. Embracing innovation while fostering teamwork and continuous improvement, CANUSDIX is a modern, goal driven, exercise regime and a model for international cooperation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".