The Current State of the “Green” Parties: Russia, Europe, the World
Bibliographic record
Abstract
The article is devoted to the study of the current state of the «green» parties in the world as a whole, as well as in Europe and the Russian Federation in particular. The history of the formation of the «green» parties is also revealed and their common features are analyzed. In addition, the difference between the European «green» parties and the Russian ones is considered there. An important part of the study is the analysis of the percentage of representatives of «green» parties in the legislative authorities in the countries. As a result of the research, the author comes to several conclusions: currently, «green» parties exist in almost half of the countries where the existence of parties is possible as such. In a quarter of these countries, representatives of these parties are in the government, and about 4% of them are in the ruling coalitions. Nevertheless, for half a century, this is quite a great achievement for parties that were once considered oppositional. Most of these parties are represented in the European parliaments, but they have a number of differences from the «green» parties of the Russian Federation, which is also noted in this article.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".