Arctic Transformations: Multinational Companies Facing the New Challenges of Sustainable Development
Bibliographic record
Abstract
What is the impact of the ongoing transformations in the Arctic region – global warming, socio-economic and institutional changes – on internationalization in the Arctic and the activities of multinational companies in the polar regions of the Arctic countries? What is the role of multinational companies in the sustainable development of these regions, including the ensuring of the welfare of the northerners? The article attempts to answer these questions and discuss new approaches to the problem of sustainable development in the Arctic region with its extremely vulnerable and severe nature, large reserves of natural resources, unique human potential, dynamically developing economy, infrastructure and active involvement in the world economy. The main emphasis is on the assessing of the social component in the triangle of the interrelated priorities of sustainable development – social, environmental and economic. The analysis showed that the consequences of systemic transformations form a new context for the activities of multinational companies, which have to adapt their corporate strategies to the Arctic specifics. The northern regions are actively involved in internationalization; a significant part of their GRP is produced by enterprises controlled by multinational companies. Assessments of the role of multinational companies for the local population and sustainable development are mixed. Such companies help to modernize the economy and infrastructure, create jobs, place orders with local producers, and develop human potential. In a number of countries, the control of the local population over the activities of multinational corporations (USA, Canada) is strengthening. At the same time, serious social and economic imbalances arise, including social disproportions and stratification of the population, as well as challenges for traditional activities and nature. The contribution of the Arctic regions to the world economy is almost five times higher than their share in the world population. Obtaining a social license from the northerners, implementing corporate social responsibility is becoming a popular instrument used by multinational companies to support their activities in the Arctic. The interaction between the state and multinational companies is strengthening, and the forms of state regulation of the access to natural resources and infrastructure are being diversified. The study is based on the analysis of the practices of foreign Arctic countries, rich in mineral and energy resources – the USA, Canada and Norway; their approaches and practices may be of interest to Russia and its northern regions. In conclusion, new scientific concepts of adaptive governance of sustainable development and its inclusiveness in the context of the interaction between transforming natural and social systems in the Arctic are summarized.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".