Rising Importance of Railways in the Eurasian Geopolitics: Potential Advantages and Risks
Bibliographic record
Abstract
Railways are becoming more important in geopolitics as a result of technological developments and the economic rise of Asian countries. Global trade is flowing from east to west as a result of the economic growth of China, which opens up new geopolitical opportunities in the Eurasian region. In 2013, with the announcement of the Belt and Road Initiative (BRI), projects and routes based on the Northern, Middle and Southern Corridors were developed. Railway transport has become an increasingly popular option in recent years as it is cheaper than air transport and shorter than maritime transport. Freight rail transport between China and Europe continued to grow during the Covid19 epidemic, reaching 222 cities in 25 European countries. Thus, with the development of rail transport, history has returned to the historical Silk Road route and has been created new geopolitical opportunities for Eurasia. In 2011, there were 17 train services between China and Europe. In 2020, the number of China-Europe freight train trips exceeded 10,000, with 4,541 trips in the first quarter of this year, up 9 per cent year-on-year. Additionally, China has begun manufacturing high-speed freight trains for the first time in the world, making high-speed freight train transportation more attractive. While railways and the BRI create potential advantages for the Eurasian geography, on the other hand, they also contain potential risks in the Eurasian geography. Especially with the outbreak of conflicts between Russia and Ukraine, problems in the Northern Corridor have come to light. On the other hand, there are various protocol and capacity problems regarding the functionality of the Middle Corridor. Furthermore, Central Asia faces various risks such as radical terrorism, coup attempts and color revolutions. Eurasian geography is predominantly terrestrial and railways are of vital importance as Eurasia acts as a bridge for the trade flowing from east to west. Although railways contribute to Eurasia's global geopolitics, their risks should also be considered. This article’s main objective is to assess the rising importance of railways in Eurasian geopolitics and the potential advantages and risks in the Northern Corridor and Middle Corridor.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".