Russian Gas Companies Strategies in the Asia-Pacific and in the Arctic under Western Sanctions and Selective Government Support
Bibliographic record
Abstract
The main purpose of this research is to determine whether Russia being under Western economic sanctions could significantly strengthen its presence in the Asia-Pacific with a pipeline gas and LNG supplies. Based on the study of the Russia’s current and planned gas projects in the eastern part of the country and in the Arctic, that are realized under sanctions’ pressure, the authors concluded that most probably by 2030 Moscow can reach this strategic objective. To resist Western sanctions against the Russian energy industry Moscow launched a program of accelerated import substitution, and as a result they have only partially achieved their goals. Considering Russia’s largest gas exporters, they resorted to different strategies to counter sanctions. The state company Gazprom postponed plans for offshore gas exploration in the Arctic and continues to prioritize gas pipeline projects which reinforce its dependence on China. In contrast, with the help from the RF government and foreign investors, the private company Novatek successfully creates a powerful infrastructure for producing LNG in the Arctic and for delivering it to Europe and the Asia-Pacific.
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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 | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".