Northern territory of the Russian Federation, Europe and America: Comparative analysis of the prospects for rural development [Северные Территории Российской Федерации, Стран Европы И Америки: Компаративистский Анализ Перспектив Сельского Развития]
Bibliographic record
Abstract
Currently, large and Nonchernozem northern European Russia and the Russian Far East and Siberia (though, like most foreign circumpolar countries) are originally desert or zapustevayuschie space in terms of rural development. On the other hand, a variety of natural, technological and demographic-migratory factors such as global warming, new technologies and social innovation, demographic change, migration can create unexpected new prospects for rural development in the northern and Russian and foreign non-black areas. The paper summarized the Russian and foreign (Scandinavian countries, Finland, USA, Canada) experience of rural development at regional and local levels, are considered public, business and non-profit programs and projects for rural development, allowing some to formulate forecasts and proposals for rural development in the northern the Russian Federation, taking into account international experience.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".