Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study analyzed educational migration in Russia. Migration is considered from the standpoint of an integrated indicator that reflects complex socio-economic processes in society. The factors of territorial mobility of the population are listed. Under their influence, the directions, dynamics, intensity and consequences of migration for donor and recipient countries change. The place and role of educational migration in the modern world are shown. The study examined the structure and dynamics of the number of foreign students studying in the universities of the Russian Federation. The directions of tough competitive struggle of national educational models in the international market of educational services and rating indicators for evaluating the activities of universities are analyzed. It is noted that the West conducts unfair competition in relation to Russian universities and the entire education system, which manifests itself in sanctions pressure, the exclusion of Russia from the Bologna process, the refusal to nostrify educational documents, etc. It is emphasized that external educational migration to a certain extent can be considered as a form of brain drain. The largest recipient countries of foreign students are indicated, which include the USA, Great Britain, China, Canada, Australia, and France.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it