Geopolitical aspects of navigation front of the Arctic in the XXI century: strategic routes for Russia and China
Bibliographic record
Abstract
The 21st century is marked by changes in matters of power balancing and system polarity, which could be explained by Geopolitical theories. In this paper, we intend to investigate how the classical Geopolitical theories – such as the Heartland/Pivot Area theory, wrote down by Halford J. Mackinder, and the Sea Power theory, wrote down by Alfred T. Mahan – could be faced and readapted amid the new settles of strategic routes and military development needs, brought by the ice-melting of the Arctic Ocean. The study cases will concentrate on Russia and China, due to their recent investments in the opening of new strategic routes for navigation and trade, including the Arctic routes, demanding inputs on technologies, transport innovation, and military emulation. Working on a qualitative method, with analysis of primary sources (such as government documents on strategies for the Arctic), and secondary sources (such as books, articles, interviews and other published materials on the topic), we hypothesize that: (i) the classical theories never predicted the ice-melting of the Arctic Ocean, perceiving it as a natural shield, and not as a navigable pathway; (ii) that the Arctic defrosting opens up new strategic routes for other countries besides Russia and China, like Canada and the United States, emerging a new conflict spot due to their different interests around this opportunity. Based on that, the preliminary results point out that: (i) it is not possible to apply the classical theories of geopolitics to these new configurations of the international system, without at least a reinterpretation/readaptation to the current context, which would alter all the power dynamics predicted by its authors; (ii) Russia and China are readequating themselves to this new scenario, in order to gain some advantages in a hypothetical dispute for the Arctic control.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".