Some migration aspects, trends and issues in the North and Central Asia: case of Kazakhstan
Bibliographic record
Abstract
Migration and mobility in the post-Soviet space are part of the global process for more than a quarter of a century. Possessing almost all the main characteristics of the global process, migrations in this space have their own characteristics and specifics that require special attention and understanding. To analyze the mobility of this space, the definitions and approaches that determine the potential systems and subsystems that cover this process are important. Kazakhstan is one of the states in this space for which migration issues and demographic development are a strategic direction, including within the framework of the Eurasian Economic Union. An important issue remains the choice of the approach that defines the given space not only geographically, but also geo-economically, and geo-politically. One of the effective in this approach can be the use of the UN definition of “North and Central Asia”, covering the main participants of the migration process. The main purpose of this article is a review of some of the main national and regional aspects of the migration processes in the Republic of Kazakhstan at the present stage. Since the beginning of the 21st century, Kazakhstan has positioned itself as a host country for migrants, being simultaneously a major transit corridor. Recently there has been a tendency of an active outflow of the population, which is a definite challenge that requires due attention and evaluation. The methodological basis of the study is a systematic approach that allows a comprehensive assessment of migration processes, as well as the theory of “pull-push factors.” This study may be important in the context of the analysis of common Central Asian processes of cooperation and integration, and from the point of view of developing a theoretical component of the migration processes. Key words: International Relations, Migration, Kazakhstan, Labor Migration, Eurasian Economic Union.
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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 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".