Implementation of COSO-ERM internal control integrated concept in Ukraine
Bibliographic record
Abstract
Introduction. At the current stage of development, the internal control system plays an important role in ensuring the effective functioning and implementation of users’ needs for information in order to make informed management decisions regarding the cost of crop production. In recent years, many scientific works have been devoted to the development of internal control at agricultural enterprises, including taking into account the adaptation of foreign experience of countries such as the USA, Japan, Germany, Poland, and Canada into domestic practice. In turn, this determines the relevance of the study of the integrated COSO-ERM model with the aim of its implementation at agricultural enterprises of Ukraine.The purpose – characterize and adapt the integrated concept of COSO-ERM internal control to the domestic practice of enterprises.Methods (methodology). The theoretical and methodological basis of scientific research is analysis, synthesis, induction, deduction, analogy, abstraction, concretization, comparison, monographic, systematic and logical methods.The results. Approaches to the organization of the system of internal control of the cost of production of crop production were studied, taking into account the principles of building its structure according to the integrated COSO-ERM model of internal control. The foreign experience of conducting internal control of the cost of crop production was adapted to the domestic practice of enterprises. Control measures have been developed to prevent or reduce agricultural production risks affecting production costs.Prospects. In the future, it is advisable to more thoroughly cover the methodology and organization of internal control of production activities of agricultural enterprises in Ukraine and in foreign countries that have positive experience.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".