Audit in the mechanism of ensuring economic security of an economic entity
Bibliographic record
Abstract
Importance. The peculiarity of modern audit is the increase in its demand by management entities, the expansion of its accompanying functions as an element of the mechanism aimed at ensuring the economic security of economic organizations of various directions. This demand is due to a number of reasons, the main of which are: the widespread spread of the globalization process to the Russian economy and the associated increased competition between manufacturers in the commodity market and in the market of audit services; the growing trend of Western countries (USA, Canada, EU countries, Japan, etc.) applying economic sanctions to Russian enterprises in violation of the rules of the world trade organization (WTO) solely for political reasons; the growth of economic information, especially with the introduction of the digital economy, which is supported by Western technologies. This blurs the information boundary between audit Analytics and industrial espionage capabilities.Objectives. The article is devoted to the study of the conceptual foundations of the theory of audit as an information tool in the management mechanism, ensuring transparency of competitive access to audit for Russian companies, the nature of the development of audit professional associations, market evaluation of mergers and acquisitions of audit self-regulatory organizations. Methodology. The achievement of these goals predetermined the use of scientific knowledge methods in research: theoretical-dialectical, formalization; empirical – observations, comparisons, systematization, study of current scientific and periodical domestic and foreign economic literature. Conclusions. Assuming that audit is an information element of the mechanism for ensuring economic security, it is important to clearly structure audit activities and the relationship of the state with audit companies, ensuring real competition in the market of audit services and protecting the information space of strategic areas of state activity. Results: the Authors revealed the specifics of mergers and acquisitions in the field of audit activity, the practice of eliminating Russian audit companies from participating in tenders, the vagueness and inconsistency of criteria and their interpretation when selecting the winners of the competition, and proposed an approach based on strengthening the impact of state institutions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".