Evaluation of the Competitive Potential of the Economic Development of the Country: Theoretical Aspects and Russian Practice
Bibliographic record
Abstract
The article presents the methodology of evaluation of the competitive potential of the regions, including the threemain stages of research, which has been tested during the analysis of competitiveness of Russian regions. Duringeach stage it is calculated the main indexes, and the Integral Index of regional competitiveness, which providethe opportunity to present a complex view of competitive advantages of the regions of the country. As the resultof this research it was presented the whole calculation of the development of Russian regions on the basis ofcompetitive ability (2010, 2012 years). Based on the calculations it was identified the main problems of Russianregional industrial development - the obsolescence of the capital assets, insufficient level of investments, the lowlevel of innovation activity of enterprises, etc. The obvious way for solving these problems is the governmentalplanning system of industrial development (industrial policy). During this research it became obvious thatpresented methodology allows making a comprehensive analysis of the competitiveness of the regions of thecountry.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".