Bibliographic record
Abstract
The article is devoted to a critically important, in the authors opinion, issue of the ethical regulation of public servants official behavior. He considers the complex of ethical-legal mechanisms as one of the most effective ways in order to correct the obviously unsatisfactory current situation of public life in this field. As long as it is not only Russias trouble and many other countries pay considerable attention to ethical aspects, the author reflects the situation in the frames of a broader theoretical position and also addresses the international experience. In particular, he gives much attention to Canada, where the ethical regulation of public service is developed sufficiently well and the country has achieved serious success in this respect. Ethical codes are considered as "moral navigators" in the contemporary complicated world, because vitality and legitimity of a political system much depends on whether political institutions and behavior of high rank public officials correspond to the prevailed public values and ideals, accord with the norms and standards of public morality, or they do not. A degree of public trust to holders of public posts depends critically on it. The administrative ethical codes of different levels and the "ethical infrastructure" that provide their fulfillment have been thoroughly analyzed. Special attention is paid to the role of the leader, to moral self-restrictions of public servants and to exercising control over them. The balance between moral and legal norms has been considered in details, as well as the modern situation of Russia in this field.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.071 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".