Foreign experience of state regulation of the wireless telecommunications sector and its use in Ukraine
Bibliographic record
Abstract
In this article, the experience of state regulation of wireless telecommunications in European countries, the US, Canada, Japan, South Korea, the UK, and others is analyzed. It was concluded that the main functions of the state in these countries are to support the development and implementation of the latest 5G and 6G mobile communication technologies, develop strategies for the development of this area, provide financial incentives for network development, adopt the necessary laws on personal data protection, ensure fair competition, and protect copyright and innovation. The main directions to reform the wireless telecommunications sector in Ukraine were identified based on the study of foreign experience, in particular: barrier-free access to infrastructure; efficient allocation of radio frequency resources; shared use of the infrastructure in this area by operators; stimulating its development by establishing tax incentives and state investments in the development of new technologies; classifying wireless telecommunications as critical infrastructure, ensuring the continuity of network operations and the protection of personal data of service users; quality control of service provision; obtaining reliable statistical information on the performance indicators of wireless telecommunications companies. It was concluded that even under martial law, the Ukrainian government managed to harmonize domestic legislation on electronic communications with the European one, classified wireless telecommunications as critical infrastructure, developed and adopted the Development Strategy for Electronic Communications until 2030, introduced national roaming to provide the population with high-quality mobile communications and the Internet, obliged operators to provide services during power outages, and promoted the spread of 4G communication services.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".