Адміністративно-правове регулювання транскордонних міграційних процесів в умовах цифровізації публічного адміністрування та забезпечення прав людини
Bibliographic record
Abstract
The article provides a comprehensive analysis of the administrative and legal regulation of cross-border migration processes in the context of digitalization of public administration and ensuring human rights. The relevance of the study is due to global migration challenges, increased population mobility in conditions of military conflicts and the development of digital technologies that transform the management of migration flows. The need for a balance between the security needs of the state and compliance with international standards in the field of human rights is emphasized. The legislation of Ukraine in the field of migration policy is analyzed, in particular the norms on the legal status of foreigners, refugees, stateless persons and administrative liability for violations of migration legislation. International legal acts such as the UN Convention on the Status of Refugees, EU Directives and the UN Global Compact on Migration are studied. Special attention is paid to the impact of digitalization on the efficiency of migration process management. The role of electronic services (Diya), electronic visa systems (eVisa), biometric control and information and analytical systems for migration management is highlighted. The importance of integrating Ukrainian information systems with European databases (Eurodac, ETIAS, EES) for strengthening control over migration flows and increasing security is emphasized. The challenges associated with the protection of personal data, ensuring cybersecurity and overcoming digital inequality among migrants are considered. It is noted that digitalization creates not only new opportunities for optimizing migration policy, but also risks to human rights and freedoms. The impact of martial law in Ukraine on cross-border migration is studied: an increase in the number of displaced persons, changes in the border crossing regime, restrictions on the mobility of certain categories of the population and the need for international support. The experience of Poland, Germany, Canada and the USA in regulating migration processes in times of crisis is analyzed. Recommendations are offered for improving Ukraine’s migration policy and the author’s conclusions are provided.
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 | 0.016 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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; both teacher heads agree on what is shown here.
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".