ADVANCING THE BERING STRAIT TUNNEL PROJECT IN THE UNITED STATES AND CANADA
Bibliographic record
Abstract
This paper investigates potential avenues of encouraging the United States and Canada (federal and local governments as well as their business and NGO communities) to consider building in stages a Bering Strait tunnel, connecting Alaska and Russia. Given that a significant government-funded phase one feasibility study in 2007 found a supportive business case for an Alaska-Canada Rail Link (ACRL) that would connect existing Canadian rail lines in British Columbia with the Alaska Railroad, the author argues that, ideally, an ACRL ought to be promoted as the first stage toward eventually building a Bering Strait crossing. Once an Alaska-Canada rail link were built, it would possibly be easier for public or private sector consideration of extension of the North American rail link from Fairbanks, Alaska to the Nome vicinity (stage two), and ultimately, to construct a tunnel to connect to Russia (stage three). However, with the business climate in western Canada now dominated by Alberta’s increased crude oil production that seeks new markets, an eventual ACRL would have to secure funding through private investment, not public funding. Given present indifference to an ACRL in North America, although it might be problematic politically, it may be a viable option to invite Chinese private investment in an ACRL. Nonetheless, ACRL construction may have to wait until several smaller-scale transportation projects are built in Alaska that will help substantiate a business case for an ACRL. On the governmental level, the project needs to be promoted strategically as a means to strengthen U.S.-Russian relations over the long-term, as well as to boost cultural ties between North America and Eurasia. A near -term recommendation is that a project office be established in Anchorage to educate and lobby Alaska’s executive and legislative branches, relevant state agencies, business and non-profit associations, Alaska native corporations, and local media for this project. It should build a base of awareness and support, including gathering a coalition of like-minded organizations and relevant state agencies. The author also recommends the Bering Strait project be cast in the broader framework of emerging U.S. policy for the Arctic region. Finally, another near-term recommendation is offered for portraying the Being Strait project as a means to reconnect the indigenous peoples of Eurasia and the Americas. Building a Bering Strait tunnel with lengthy connecting railways in North America and Eurasia will require the political and financial support from within the three nations whose territory the project will traverse: the United States, Canada, and Russia (China is arguably the fourth nation whose financing and labor may be essential for undertaking this project on the Eurasian side). This paper makes recommendations how to promote and advance this project within the U.S. and Canada, with a focus on the State of Alaska, as well as British Columbia, Alberta, and the Yukon territory. It also discusses serious impediments in the current political and economic climate toward constructing the first stage of a Bering Strait project: the connection of the rail lines between Alaska and British Columbia. The U.S. and Canada, as democracies, will require a multifaceted approach that utilizes effective and sustained education and lobbying in the public and and private sector to build support, obtain financing and governmental approvals for this project to succeed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".