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Indian Interest in the Arctic in the Context of China’s Arctic Policy

2017· article· en· W2775034049 on OpenAlexaboutno aff
Н. А. Николаев

Bibliographic record

VenuePost-Soviet Issues · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChinaArcticRivalryContext (archaeology)GeographyThe arcticPolitical scienceDistribution (mathematics)Development economicsEconomyInternational tradeEconomic growthBusinessEconomicsOceanographyLaw

Abstract

fetched live from OpenAlex

The study examines the general and excellent in the Arctic policy of India and China and the likelihood of rivalry between the two Asian powers in the allocation of resources to the Arctic. Also, Indian and Chinese research trends on Arctic topics were considered. Since the middle of XX century. India and China act as long-standing rivals. Periodically, military clashes broke out between the two sides on a common border. Despite the fact that the key territorial issues on the common border between India and China are resolved military provocations from both sides do not stop. The latest incident was the transfer of Indian troops to the Chinese border zone in the province of Sikkim. Both powers of Asia are major consumers of energy resources, they are more or less interested in the situation on the global energy market. In the Arctic there are colossal reserves of various resources. Certain difficulties and limitations with access to resources and their equitable distribution can force these countries to compete with each other. However, the lack of a specific position on Arctic issues or the formulated regional strategy for India and China creates a lot of doubt about their true intentions. The study of research trends, the activity of Indian and Chinese business structures, as well as the arctic activities of India and China, gives approximate answers to this question. The potentials of India and China are very different in the Arctic. China’s strengths are active participation in international scientific research, the availability of a qualified ice-class crew, active investment in energy and infrastructure projects in the Arctic countries, and fairly stable trade relations with most Arctic countries. The weak side of China is its negative image. Residents of many Arctic countries are very wary of the «rise of China» and its growing interest in the Arctic. Strengths of India are a positive image and a representative diaspora in the Arctic countries, especially in the US and Canada. In the future this will allow Delhi to successfully promote initiatives in the Arctic. The weak side of India can be considered the absence of a ship «icebreaker class», the weak investment activity of Indian business structures and poor knowledge of Arctic problems from the point of view of Indian issues.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.629
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.059
GPT teacher head0.381
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2017
Admission routes1
Has abstractyes

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