Population of Kalmykia: Main Geodemographic Trends of the First Quarter of the 21st Century
Bibliographic record
Abstract
The article analyzes the main trends in the quantitative, spatial, and settlement dynamics of the population of Kalmykia in the first quarter of the 21 st century. It was found that migration was the main factor of geodemographic changes. The active outflow of population determined the increased rate of demographic losses in the republic (8.8% for 2002–2024 was the highest rate among regions in the South of Russia), despite the maintenance of a positive natural growth rate until the early 2020s. A slight reduction in the scale of migration loss in the 2000s and its new growth in the 2010s make it possible to identify two periods in the demographic dynamics of the republic’s population, which generally coincide with the first two decades of the 21 st century. The outflow of population was widespread, but its intensity varied significantly across the territory of Kalmykia. The maximum demographic losses (21–30%) in the first quarter of the century were suffered by the western and northwestern districts (Gorodovikovsky, Priyutnensky, Sarpinsky, Ketcherovsky), in which significant outflow was combined with a natural decrease in the population due to its national structure (high proportion of Russians). In the inter-regional exchange, all the territorial communities of Kalmykia, including the capital, lost their population. In the intraregional population circulation, the metropolitan agglomeration was the only significant center of population attraction in the 2000s–2020s. Moreover, the outflow from Elista was the largest, which compensated for this loss with an influx of internal migrants. This process contributed to the increasing concentration of demographic potential in Elista and its satellite village of Troitsk (in 1989–2024 their share in the population of the republic increased from 31.5 to 45.2%). A similar process took place at the local level – in 2024, 53.9% of rural residents were already concentrated in district centers (in 1989 – 42.2%). The limited scale of the republican labor market, due to small socio-economic potential of Kalmykia; difficult life conditions and economic activity of the population, determine the stability of the migration outflow, which will most likely maintain the republic in the position of the southern Russian region with the highest rates of general depopulation until 2040–2045.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".