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PROBLEMS OF THE ECONOMIC SUSTAINABILITY OF CANADIAN ARCTIC REGIONS

2022· article· en· W4205575121 on OpenAlexaboutno aff
Andrey O. Podoplekin

Bibliographic record

VenueActual directions of scientific researches of the XXI century theory and practice · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCircumpolar starArcticPopulationSustainabilityModernization theoryHuman settlementDiversification (marketing strategy)Public sectorBusinessEconomyEconomic growthGeographyEconomics

Abstract

fetched live from OpenAlex

The article examines the key issues and risks of the governing and socio-economic development of the Canadian Arctic regions. The relevance of this subject is determined by scientific and practical interest in adapting in Russia the most effective approaches and practices for realizing the economic potential of circumpolar regions in foreign countries. With regard to areas of the Arctic zone of the Russian Federation (characterized by low population density of vast areas, the absence of large urban settlements with scientific and cultural centers, undeveloped ground transport infrastructure, extreme climatic and geological conditions, the absence of large industrial and energy facilities) special interest represents the relevant Canadian experience. The article shows that in the 2000s, Canada did not come close to turning industry into a leading factor in the economy of the Arctic territories. At the same time, a series of federal programs for the modernization of social and transport infrastructure also did not become a significant incentive for the development of the northern regions. As federal statistics shows, the largest share of their GRP is still formed in the public sector, and the degree of diversification of the regional economy remains extremely low. The modern economy of the circumpolar Canada is based on the dominance of the state in investments and stimulating consumer demand. The consequence of this is an increase in wages, provoking an increase in the cost of all goods and the cost of living in general. Small businesses are unable to compete with the public sector for labor, which constrains private entrepreneurship. For Canada, the Arctic has not yet become the driver of national economic growth, and the lack of infrastructure is a serious obstacle to large-scale investment.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.086
Threshold uncertainty score0.622

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.007
Science and technology studies0.0160.005
Scholarly communication0.0100.002
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.048
GPT teacher head0.341
Teacher spread0.293 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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