MétaCan
Menu
Back to cohort

Geographical and Legal Problems of Delimitation of the Arctic Territories in the Krasnoyarsk Territory (Krai)

2016· article· en· W2548574643 on OpenAlexaboutno aff
Л. А. Безруков

Bibliographic record

VenueJournal of Siberian Federal University Humanities & Social Sciences · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
FundersRussian Humanitarian Foundation
KeywordsGeographyArcticThe arcticArchaeologyEnvironmental protectionEcologyGeologyOceanographyBiology

Abstract

fetched live from OpenAlex

The present study deals with the geographical and legal problems of delimitation of the North and Arctic territories in the Krasnoyarsk Territory (Krai). With respect to the legislative delimitation of the North as a separate entity, it provides characteristics the three main latitude zones of the Krasnoyarsk Territory (Krai): the South (the Southern Latitude Belt), the Near North, and the Far (Extreme) North, along with the respective principles of territorial policy. The emphasis is placed on the insufficient substantiation of the "Arctic zone" delimitation on land, especially on the existing contradictions between its boundaries and the boundaries of the Extreme North zone. The article also explores the problem of political and legal regulation as regards the demarcation of the water area of the Arctic Ocean, which arose after the entry of the 1982 UN Convention on the Law of the Sea (UNCLOS) into force, as its principal provisions were fundamentally different from the historically established division of the Arctic into five polar sectors belonging to Russia, Canada, the USA, Denmark and Norway. Some issues related to the influence of the differences in the Arctic maritime spaces' legal status on the peculiarities of the development of their natural resources are also covered.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.007
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.035
GPT teacher head0.262
Teacher spread0.227 · 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; both teacher heads agree on what is shown here.

Study designObservational
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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Siberian Federal University Humanities & Social SciencesSame topicArctic and Russian Policy StudiesFrench-language works237,207