Conceptual foundations of the policy of voluntary resettlement of compatriots at the present stage of development of the Russian Federation
Bibliographic record
Abstract
The study examines the conceptual political and legal foundations for the formation and implementation of state policy on the voluntary resettlement of compatriots. One of the main tasks of this direction of state policy at the present stage is the return and attraction to the state of persons in demand by the economy and ready for faster integration into the host society, which actualizes the need to develop resettlement programs not only for potential compatriots currently living in the territories of post-Soviet states or states of Western Europe, the USA and Canada, but also , the creation of mechanisms for the resettlement of foreigners who are not included in the category of “compatriot”, but nevertheless, ready to integrate into Russian society, having a similar cultural code. The theoretical and methodological basis of the research is formed in the paradigm of understanding the state policy on the voluntary resettlement of compatriots as an integral part of the migration policy of the state, which determines the use of approaches characteristic of various disciplines to the study of migration as an interdisciplinary phenomenon. Institutional and comparative approaches were used as the main approaches to scientific research adopted at the level of classical political science. Induction, deduction, analysis and synthesis are also reflected in the study. In the article, the state policy of voluntary resettlement of compatriots from abroad is considered from the point of view of solving the strategic tasks of the state in terms of increasing human capital, solving demographic problems and spatial development. The development of effective appropriate solutions in the analyzed area is the result not only of the application of a formal legal approach typical for the adjustment of migration legislation, but also of comparative studies involving the selection and co-optation of the most successful resettlement practices of foreign countries. At the same time, the narratives of the “Russian World” as a source of formation of a new civic community become the ideological concept of a new approach to the repatriation of persons of these categories.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".