Territorial Shifts in Anthropogenic Pressure on the Environment in Post-Soviet Russia
Bibliographic record
Abstract
Abstract The changes in production and population in Russian regions for the years 1990–2020 are considered as an indirect indicator of the changes in the total anthropogenic pressure on the environment. It is shown that the pressure increases primarily in well-developed territories and decreases in vast underdeveloped areas. A new environmentally unfavorable trend in environmental pressures is the relative shift to coastal regions, i.e., to the vulnerable and recreationally attractive coasts of the Atlantic seas as well as the Caspian Sea. Simultaneously, there is a clear northeastern vector in the development of the mining industry, which leads to the formation of new local centers of large-scale impacts on ecologically significant and vulnerable landscapes of East Siberia, the Far East, the European North, and the shelf zones. In the 21st century, most of the main mining regions have increased their extraction of mineral resources: half of them by 50% or more and a quarter by 200% or more. It is shown that the environmental situation is more likely to deteriorate further in the regions with a strong increase in anthropogenic pressure than it is to improve in the regions that are now leaders in terms of reducing adverse impacts.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".