MétaCan
Menu
Back to cohort
Record W7135844463

Geopolitics in the Arctic - the evolution of A5 countries' claims to an extended continental shelf in the Arctic Ocean

2024· dissertation· cs· W7135844463 on OpenAlexaboutno aff
Ema Kotková

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2024
Typedissertation
Languagecs
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeopoliticsArcticUnited Nations Convention on the Law of the SeaContinental shelfInternational lawThe arcticConvention
DOInot available

Abstract

fetched live from OpenAlex

This bachelor's thesis examines the territorial claims of the seabed, or extended continental shelf, in the Arctic Ocean and the current geopolitical situation between Russia and the western countries - specifically the United States and Canada - in the Arctic region. The thesis aims to map the development of the extended continental shelf proposals of all the Arctic Five countries - Norway, Russia, Denmark, Canada and the United States (A5) and at the same time to trace the approach of each A5 country to the United Nations Convention on the Law of the Sea (UNCLOS), as the approach of the respective A5 countries to UNCLOS differs. The second part of the thesis focuses on Russia's current geopolitics in the Arctic and the relationship between Russia and the two major western players in Arctic geopolitics, which is examined through a content analysis of official contributions from the governments of Russia, Canada, and the United States. The analysis shows that Arctic geopolitics has changed a great deal over the last three years and the whole situation is more heated than it was, helped by the currently tense atmosphere between East and West. Keywords: extended continental shelf, Article 76 of the UN Convention on the Law of the Sea, A5, geopolitics

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0040.005
Scholarly communication0.0060.002
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.285
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueDigital Repository (National Repository of Grey Literature)Same topicArctic and Russian Policy StudiesFrench-language works237,207