THE POWER METRICS OF THE RUSSIAN FEDERATION TOWARDS THE G7 OVER THE PERIOD 1992–2020
Bibliographic record
Abstract
This paper deals with the subject of the strength of the key world powers in the years 1992-2020. These include the G7 group and the Russian Federation, which was suspended from the group, and so far has not been authorized to resume meetings with the G7 group. In this period, after Russia's exclusion, both regional and global rivalry grew in the world. This translated into the global imbalance of power and an overall geopolitical situation. In this paper, the author proposes a quantification of the power to measure power metrics. Based on the data from the World Bank and Military Balance, the general (economic), military and geopolitical potential of the Russian Federation, Canada, France, Germany, Italy, Japan, Great Britain and the United States was developed. The model of Mirosaw Suek was applied to calculate the power, which reflects the objective reasons for changes in shaping the potential of the aforementioned countries. The purpose of this article was to determine the changes in the power of the G7 countries and the Russian Federation in the years 1992-2020. This translated into the international balance of power and the struggle for influence in the world.
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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 | 0.001 | 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 | 0.022 | 0.006 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".