Bibliographic record
Abstract
The net migration inflow to the Russian Federation stood at 270 000 persons in 2014, according to official Rosstat statistics. While net immigration was lower than in 2013 (when it stood at 296 000), the gross migration inflow and outflow were both higher in 2014 than in 2013. The migration inflow in 2014 reached 578 000, an increase of 20% over the 2013 level. Immigrants in 2014 mainly came from other CIS countries: Uzbekistan (131 000 persons), followed by Ukraine, Kazakhstan and Tajikistan. Among non-CIS countries, People’s Republic of China was the main origin of immigrants (11 000 persons). As in 2013, immigrants from Uzbekistan accounted for one-quarter of the entire inflow. At 308 000 persons, the migration outflow was particularly high in 2014, likely because foreign workers whose registration expires are counted as emigrants. The outflow was mainly directed to the CIS countries of Uzbekistan (94 000), Tajikistan (35 000) and Ukraine (30 000), and to China (9 000). The highest net inflow from any country came from Ukraine (80 000).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.161 | 0.128 |
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".