ЗАРУБІЖНИЙ ДОСВІД ДОТРИМАННЯ ПРИНЦИПІВ ПРОЗОРОСТІ ТА ВІДКРИТОСТІ В ДІЯЛЬНОСТІ ОРГАНІВ ПУБЛІЧНОЇ ВЛАДИ
Bibliographic record
Abstract
The article examines the experience of foreign countries in adhering to the principles of transparency and open-ness in the activities of public authorities. We have systematized components of transparency and it became clear that one of the components, which indi-cates the level of transparency, is open data. This means the availability of information on the activities of public au-thorities. Data disclosure raises the level of transparency and accountability on the activities of public authorities, promotes more efficient use of public resources, improves the quality of public services, as well as promotes the de-velopment of innovative business and the creation of socially useful services. Index of competitiveness of the coun-tries of the world in the global economic rating is calculated on the basis of open data. The next component of transparency is user-friendly information. Its core is to inform citizens and their col-leagues about the planned decisions of public authorities and how they are going to be implemented in accessible form of understanding. The third component of transparency is the awareness of citizens, which is manifested in the ability of public au-thorities to provide information to citizens in terms of the principles of rule of law and strengthening the capacity of civil society. We have considered annual international rating Open Data Barometer, which describes the condition of develop-ment of open data in the countries of the world, and we have estimated that the United Kingdom, Canada, France, the United States of America, Korea are leaders in terms of the level of development of open data, readiness of open data and index of influence on business, politics and civil society. We have characterized the levels of transparency, in particular organizational and normative. We have analyzed normative legal acts of developed countries of the world regulating access to public infor-mation. We have determined that there are no unified approach to solve the issue of legislative consolidation of proce-dures providing access to information in foreign countries, but the methods and forms of public involvement in online consultations differ from country to country and within the apparatus of public administration that is connected with the national traditions of forming the principles of transparency and openness of public authorities, knowledge and skills of civil officers and potential participants in consultations, available technical capabilities, subjective and objec-tive factors. We have determined that the practice of legal regulation in each country has its own characteristics, depending on the history of society development, cultural and mental traditions, and, taking into account this, cannot be automati-cally extended to the management norms in domestic legislation
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.053 |
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".