PRIORITY RATING OF COUNTRIES OF THE WORLD FOR UKRAINE’S NATIONAL INTERESTS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
After the Russian occupation of Crimea and a part of Donbas the political and geographical position of Ukraine as well as its positioning in the modern world significantly changed. Previously, Ukraine had placed greater focus on non-bloc status in the multipolar world and on development of mutually beneficial bilateral relations with all its partners. For this reason, it is very important to calculate the country priority rating for Ukraine. This rating contains two groups of indicators from all spheres of interstate relations. The first group shows the current level of interaction and the second group shows the importance of states in the modern world. From six priority groups of countries the top-priority for Ukraine is cooperation with Germany, the USA, the United Kingdom, the Netherlands, Italy, France, Canada, Spain and Switzerland. The second priority group includes most of European countries (such as the Czech Republic, Poland, Austria, Belgium, Sweden, Denmark, Portugal, Hungary, Romania, Norway, Iceland, Finland, Slovakia), Japan, Israel, Australia, South Korea, Turkey and Singapore. Contrary to popular belief of supporters of indispensable friendship with Russia this country is not so important for cooperation nowadays and, moreover, it is not a landmark for the future as it is only in the third priority group. This group also includes Bulgaria, Malaysia, China, New Zealand, Estonia, Greece, Latvia, Thailand, Brazil, etc.Cooperation with more prosperous countries will help to get rid of the negative moments of Russian colonization, to reach higher economic and socio-political standards. With certain modifications this rating can be used for calculation of cooperation priority ratings for any country in the world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it