The selectivity of attracting foreign nationals to work in recipient countries
Bibliographic record
Abstract
The article provides a comparative analysis of practices on regulating the employment of foreign nationals, used in large recipient states (Germany, USA, Canada, Russia, Republic of Korea). The subject of the study is the process of external labor migration, taking into account country regulatory approaches to attracting foreign labour. The study aims to develop theoretical principles and methodology for regulating the process of external labor migration. The methodology is based on the polyparadigmal concept of the study, using theoretical experience in the study of migration processes and the practice of influencing their regulation. The scientific novelty of the study is to assess the effectiveness of a selective approach to attracting foreign workers to national labour markets. As a result of the study, a methodology has been developed to assess the impact of migration processes on labour market regulation in recipient countries. Promising for countries hosting external migrant workers is the mechanism of targeted organized recruitment of foreign nationals to carry out work activities. At the heart of this mechanism is the selective selection of job seekers on the basis of professional, sociocultural, educational and personal criteria that correspond to the interests of the host external migrants of society and the recipient state. To understand the basic administrative approaches and the system of economic, legal and social instruments for regulating the process of external labour migration, it is important to study the practice of adaptation activities of large recipient States, which have a systematic and proven mechanism of inclusion of foreign job seekers. Measures to regulate external labour migration needed to be balanced, since increased restrictive measures could lead to an increase in illegal external labour migration, and excessive preferences for foreign workers could restrict the rights of recipient citizens.
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.
How this classification was reachedexpand
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 | 0.002 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".