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Record W2332605846 · doi:10.17059/2014-2-9

Comparative estimates of Kamchatka territory development in the context of northern territories of foreign countries

2014· article· en· W2332605846 on OpenAlexaboutno aff
А. Г. Шеломенцев, Olga Kozlova, Tatyana Terentyeva, Ye. B. Bedrina

Bibliographic record

VenueEconomy of Regions · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyContext (archaeology)Regional scienceEconomic geographyArchaeology

Abstract

fetched live from OpenAlex

The article promotes an approach to assess the prospects of regional development on the basis of the synthesis of comparative and historical methods of research. According to the authors, the comparative analysis of the similar functioning of the socio-economic systems forms deeper understanding what part factors and methods of state regulation play in regional development, and also their place in socio-economic and geopolitical space. The object of the research is Kamchatka territory as the region playing strategically important role in socio-economic development of Russia and also northern territories of the other countries comparable with Kamchatka on the bass if environmental conditions such as Iceland, Greenland, USA (Alaska), Canada (Yukon), and Japan (Hokkaido). On the basis of allocation of the general signs of regional socio-economic systems and creation of the regional development models forming the basis for comparative estimates, the article analyses the territories, which are comparable on the base of climatic, geographic, economic, geopolitical conditions, but thus significantly different due to the level of economic familiarity. The generalization of the extensive statistical material characterizing various spheres of activity at these territories, including branch structure of the economy, its infrastructure security, demographic situation, the budgetary and financial sphere are given. It allows defining the crucial features of the regional economy development models. In the conclusion, the authors emphasize that ignoring of the essential relations among the regional system elements and internal and external factors deprives a research of historical and socio-economic basis.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.007
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.035
GPT teacher head0.296
Teacher spread0.262 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

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