Comparative estimates of Kamchatka territory development in the context of northern territories of foreign countries
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".