INTEGRATED ASSESSMENT OF THE RUSSIAN ECONOMY COMPETITIVENESS
Bibliographic record
Abstract
In the context of the modern economic processes development at the regional level, such an aspect as regional competitiveness plays an extremely important role. To quantify the competitiveness of the regions of the Russian Federation, 10 subjects were taken. A comparative analysis was carried out on the basis of 35 indicators divided into 7 blocks depending on factor affiliation. The result of the analysis is the ranking of the considered regions of the Russian Federation in terms of competitiveness.The quantitative analysis carried out in conjunction with a qualitative assessment based on the SWOT analysis allows us to create a relatively clear picture of the competitiveness ratio of individual Russian regions, the main characteristic of which is their rather strong differentiation, due to the geoeconomic features already mentioned above. One can use the successful experience of countries such as Canada, China and Ireland in the formation of directions considered in this paper for increasing the competitiveness of regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".