The human right to «good governance»: concept and the normative content
Bibliographic record
Abstract
The article analyzes the concept of the right to «good governance», which recently been restatedin the regulations of the European Union as one of the «new» human rights. The authors examine therelationship of this right to constitutional acts of states and the European Union regulatory documents, as well as features of the normative content of the right to «good governance» in accordance with theEU Charter of Fundamental Rights in 2000. The right to «good governance» was initially secured in theconstitutional acts of the countries of the British Commonwealth of Nations, and then spread to the constitutionalacts of other states. Thus, the authors cite the constitutional acts of Canada, Greece, Andorraas an example. The analogy of the right to «good governance» is also fixed in the constitutions of the RussianFederation and the Republic of Kazakhstan. According to the authors the right to «good governance»refers to the category of first-generation rights, because it is in a certain sense, a logical continuation ofthe constitutional right of citizens to participate in managing state affairs, in relation to such integrationassociations such as the European Union. The article points to the existing relationship between the rightto «good governance» and the internal and external functions of the state.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.073 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".