I distance application in the ranking of Group 8 and European Union countries by level of development
Bibliographic record
Abstract
Abstract According to the analyses published by the international organizations, the most developed countries are those from Group 8. The group of highly developed countries is in matter, which consists of: Japan, USA, Russia, Great Britain, Italy, Germany, France and Canada. The goal of the work is to determine the ranking list of the selected countries according to the level of development in 2021 based on a certain number of macroeconomic factors. For the purposes of realizing the formulated goal, the I distance method was applied. A decision for the I distance method comes from the fact that this model satisfies all the conditions characteristic for the nature of distance, that is, for the multidimensional phenomenon of development. Based on the ranking list of Group 8 countries, the United States of America is in the first place, followed by Germany, France, the United Kingdom, Italy, Canada, the Russian Federation and Japan. Speaking about the EU countries, the Netherlands has the highest level of development according to the selected indicators, followed by Ireland, Belgium, Spain, Poland, Sweden, Austria, Denmark, Czech Republic, Luxembourg etc. The coming future will probably bring changes when it comes to the ranking on the ranking list. Changes can be expected due to the war events, demographic trends, technological achievements, and generally the replacement of the leading positions when it comes to resources. Namely, it is certain that the countries that adapt faster to other energy sources as well as to more economical use of the existing ones, will have a leading role on a global scale.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".