Internal Political and International Aspects of Regulation of the Shadow Sector as a Threat to Economic Security
Bibliographic record
Abstract
The purpose of this research is to develop methodologies for the development of regulatory mechanisms of theshadow economy in Russia from the viewpoint of the theory of economic interests. To implement the set goalshave been resolved following scientific problems:• Analysis of mechanisms of regulation of shadow economic relations in the Russian Federation.• To develop methodological basis of the theory of economic interests in the informal sector of the RussianFederation and to formulate practical recommendations for their effective implementation.• To analyze the patterns of development of economic relations in the informal sectors of the Russian Federation.• Identify actions the improvement of the tools of regulation of economic policy in the informal sectors of theRussian Federation.• Develop a methodology to neutralize shadow relations as the basis for the correction of imbalances economicinterests in Russia.Theoretic-methodological basis of the study was the theory of economic interests, which is a research programfounded on the principles of relativism, scientific attractiveness as research methodology problems of influenceof shadow economic relations at the national economic security is the ability of dialectical synthesis, which nomethodology of
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 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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".