Bibliographic record
Abstract
The development of administrative jurisdiction is extremely important for the establishment of a democratic society and the protection of human rights. The purpose of this paper was to study the system of administrative courts in Ukraine and other countries and delineate the powers of courts of different jurisdictions, as well as to study the history of the system of administrative courts in different countries and compare the experience of administrative jurisdictions in different countries. The methodological framework comprised discourse analysis as a method of qualitative research of the issues under consideration. This method involves the study of textual sources, mainly when it comes to understanding law and social laws, as well as their history. In the course of the study, the systems of construction of administrative proceedings of the leading European countries are considered, based on which the general systems of organisation of administrative jurisdiction are outlined: 1) French; 2) German; 3) the common law system; 4) different types of mixed systems. As a result of the research it was established that in general the development of administrative jurisdiction in Ukraine from the 19th century to the present has passed 5 stages and each of them was described. It is stated that the current system of administrative jurisdiction in Ukraine is quite progressive and balanced: administrative courts are a separate three-tier system, and a special procedure has been introduced for administrative cases.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".