Selling Energy to China: Chinese Energy Politics in the Arctic
Bibliographic record
Abstract
Abstract Until recently, the Arctic including the Arctic Ocean was only mentioned in the context of global warming. However, global warming has led to a thawing of ice that unveiled great findings of natural resources. The Arctic is now in the middle of a rapid environmental, geopolitical and economic transformation. The planting of the Russian flag by Russian researchers in 2007 on the bottom of the Artic Ocean triggered an overwhelming attention from other actors and states outside the region. Within a short time, all the Arctic countries, the US, Canada, Denmark (Greenland), Iceland, Norway, Sweden, Finland and Russia, have all developed their own Artic strategy and outside actors have voiced their interest for influence in the region. One outside actor that has had a great presence in the Arctic region is China. China has signed bilateral agreements with several of the Arctic states and shown growing interest in the development of Arctic natural resources. Beijing does not have an official Arctic strategy, and the Arctic countries, as well as the global community, are curious about what China s intention is in the region. In this thesis, I analyse the Icelandic, Russian and, supposedly, Chinese Arctic strategy; what is China s role in these two Arctic countries strategy and what do the activities in the Arctic mean to China. The thesis shows that, for both Iceland and Russia, China appears like the partner that best suits their strategic priorities. In Iceland s case, China is the only country that has both the technology and the economic capacity to develop Icelandic resources. Chinese presence in the Arctic supports two of Iceland s primary Arctic priorities: the legitimisation of Iceland as a coastal Arctic state and preventing the region from becoming an exclusive region just for the Arctic littoral states, that are the US, Canada, Russia, Denmark (Greenland), Norway and Russia. Russia is undoubtedly the country that possesses the biggest share of the Arctic s riches. Early on, Russia was flirting with international companies with licenses in the Arctic region. However, in the light of the Crimea annexation in 2014, the Western sanctions that followed ignited a series of bilateral agreements with China that makes it seem like the beginning of Russia s pivot towards the East. Both Iceland and Russia are looking for a partner who can boost their economy and help them achieve their strategic goals; develop natural resources and, as a consequence, boost socio-economic developments. The findings in this thesis show that Chinese companies have a strong advantage in the Arctic compared to other companies. The Chinese companies are eager to make foreign investments and have deep enough pockets to support potential projects. Simultaneously, their investments receive great support from Beijing, and China s political leaders work actively at improving diplomatic relations and make use of China s strongest card, economic wealth and access to the world s biggest market.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".