Management of Reputation Risks at the Agricultural Enterprises of Eastern Europe as a Component of Increasing Their Competitiveness
Bibliographic record
Abstract
We note a significant role of the agricultural sector in the development of economic systems in a significant number of post-Soviet countries of Eastern Europe. However, Eastern European agricultural enterprises have significant problems in ensuring and managing their competitiveness, where reputation and the risks associated with it are of key importance. Novelty. The scientific novelty of the research paper is the developed algorithm of reputation risk management, which is based on the author's methodology of their evaluation and takes into account the peculiarities of such management in agricultural enterprises from the post-Soviet countries of Eastern Europe. To achieve the goal and test the hypotheses put forward in the research paper, a set of general, specific and technical methods were used at the empirical and theoretical levels, such as: abstraction method; expert method; methods of analysis and synthesis; comparison; deduction; induction; methods of systematization, grouping and logical generalization. The research methodology is based on systemic and functional, historical and systemic approaches in identifying and resolving the range of problems of reputation risk management within the framework of improving the competitiveness management of agro-industrial enterprises from the post-Soviet countries of Eastern Europe. For the purpose of the study, data were collected and an empirical analysis was conducted concerning the eleven Eastern European countries that were part of the Soviet Union for 1991-2018 regarding analysis of the dynamics of agricultural production and its share in GDP according to statistics taken from the KNOEMA databases. Policy considerations: the agricultural sector of the economy plays an increasing role in the economic systems of some post-Soviet countries of Eastern Europe, serving as the basis for their sustainable development; agricultural producers from the post-Soviet space of Eastern Europe have problems with ensuring competitiveness in national, international and world markets; reputation risk plays a significant role in ensuring and improving the competitiveness management of agricultural enterprises from post-Soviet countries of Eastern Europe; the formation of an effective reputation risk management algorithm is a key element in ensuring and improving the competitiveness management of Eastern European agricultural producers.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".