Evaluation of Russian Foreign Trade Activities from 2000 to 2013
Bibliographic record
Abstract
The current state of Russian economy determines the necessity of evaluation of foreign trade policy, which is a crucial component of industrial regulation. This formed the purpose of the research – the identifying of the opportunities for intensification of Russia’s participation in the regional integration process through a comparative analysis of the development of the foreign trade relations of the Russian regions in the period from 2000 to the present time. Analysis of interregional cooperation of Russian regions showed that there is a trade deficit in most regions. In most regions there is а focus on the export of resources and irrational structure of imports, which promotes the preservation of the inertial scenario of expansion of foreign economic activity of the regions and the country as a whole. The growth of exports is implementedat higher ratescompared to the growth of imports. Consequently, Russian foreign trade, which had a stable export orientation previously, has become even more export-oriented. Russian Federation despite the status of a major industrial power has actually become a mono-cultural exporter. With such high concentration of exports in a small group of commodities and materials to Russia the scope of maneuver into the foreign economic relations significantly narrows and its vulnerability against the negative changes in the world conjuncture greatly increases. In addition, high deterioration of external conjuncture of the energy export was a cause of a number of serious systemic risks for domestic economy and finally may be a cause of deep economic crisis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| 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) | 0.002 | 0.001 |
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".