STATE AUDIT IN THE FIELD OF ASSESSING THE EFFECTIVENESS OF THE USE OF NATURAL RESOURCES: WORLD EXPERIENCE
Bibliographic record
Abstract
Against the background of globalization of trends in the transition to «green» technologies and the economy, the increase in related costs, the relevance of assessing the effectiveness of audit activities in the environmental sphere is also increasing. In this regard, the article examines the world experience in organizing and conducting a state audit of the efficiency of the use of natural resources. In particular, the authors consider the methodological approaches of the supreme audit institutions of foreign countries that occupy high positions in international ratings of environmental protection and the use of resource-saving technologies. As a result of the study, it was revealed that most of the external state audit bodies do not conduct an audit of the use of natural resources, not in the form of a separate type of audit, but as an audit of efficiency. In some cases, these audits combine elements of an efficiency audit and a compliance audit, as well as a financial audit. At the same time, in the structure of the efficiency audit elements used in the activities of the supreme audit institutions of the countries under study, «economy», «efficiency» and «efficiency» can be distinguished, with the exception of the experience of Canada, whose audit management adds «environment» and «sustainable development». Based on the results of the analysis, the authors formulated conclusions in the context of considering the possibility of adapting the best best practices of the Supreme Audit Institutions in domestic conditions in the field of assessing the effectiveness of the use of natural resources and environmental protection measures in general.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".