Эмиграция молодежи из Таджикистана в страны Организации экономического сотрудничества и развития: история и современные тренды
Bibliographic record
Abstract
Introduction. Being a country with a young age structure, Tajikistan has become a prominent participant of various migration flows in recent years. A large number of labor migrants from Tajikistan to the member countries of the Organization for Economic Cooperation and Development (OECD) have been reported since 2014, which is associated with a fall in the ruble’s exchange rate and a decrease in incomes of migrants to Russia in currency equivalent. At the same time, traditionally Tajik youth used to to study in Russia and Kazakhstan, but in recent decades the flow to OECD member countries has also increased significantly. Goals. The study aims to identify the causes and features underlying the reorientation of the flows of educational migrants from Tajikistan toward new geographical directions, namely the OECD member countries. Materials and methods. The work basically employs two research methods. Firstly, the statistical method processes data on the scope and structure of educational emigration from Tajikistan. Secondly, the sociological method provides insights into outcomes of sociological surveys and expert interviews (secondary analysis of sociological data). The key sources of information are OECD-related data from the OECD.Stat reports, and the author’s survey (conducted online via Facebook social network — banned in Russia — accounts of several associations of Tajik citizens abroad) among young individuals from Tajikistan who study in OECD member countries. The questionnaire contained 17 questions about adaptation and integration of migrants, educational levels of migrants, age-sex structure, migration channels, reasons for the reorientation of labor migrants toward OECD member countries, resettlement, and sectoral employment in host countries. The convenience sampling yielded a total of was 417 individuals who were then undertaking training programs in Austria, Germany, the U.S., and Canada. The survey was primarily seeking to identify adaptation strategies selected by young emigrants from Tajikistan in OECD member countries. Results. So, the article presents the outcomes of the survey. Half of Tajik university graduates try to continue their studies and/or find a job abroad via the Internet. Actually, many tend to view educational migration as an emigration channel. This process is accompanied by that Tajik citizens take additional training or retraining programs, seek to receive acknowledgement certificates for diplomas of Tajikistan, and undergo corresponding courses in the receiving countries. As a rule, they quickly adapt to labor markets in OECD member countries: it takes ‘less than a month’ (or ‘from 1 to 3 months’) to get a job. The working language for most Tajik migrants is English and German, and they get jobs in the fields of education and medicine, which attests to somewhat increased educational levels of theirs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.008 |
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".