PUTTING PEOPLE LAST: LESSONS FROM THE REGULATION OF MIGRATION IN RUSSIA AND TAJIKISTAN
Bibliographic record
Abstract
This paper analyses the recent developments and general direction of migration policy in two former Soviet Union countries – Russia and Tajikistan – from the lens of the current narrative in the field of migration research, paying attention to the economic and demographic reasons for migration, its legal and political framework, and the nascent integration and inclusion programs. While explaining the roots of the existing migration policy, and distinguishing between the migration policies of sending and receiving countries, the paper defines such terms as migration regime, migration mechanisms and migration regulations. The paper concludes that Russian migration policy reflects the inconsistency between the de jure liberal principles/ norms and their de facto restrictive application. The deeply embedded desire to limit an influx of the “Other” in Russia presents a serious threat to migration policy and the future economic development of the country. By contrast, while developing a comprehensive legislation, Tajikistan lacks the political will and resources to monitor its implementation and progressively demand the delivery of the results.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".