Lobbist Organizations as Conflict Resolution Institute
Bibliographic record
Abstract
The study specified in this article is devoted to an important problem in the modern state management practice of Russia - the study of conflict resolution of such a politically significant institute as lobbist organizations. The authors consider the phenomenon from a socio-economic, organizational, political perspective, which is categorized through the conceptual series “government relations - public administration - political institute” and is scientifically justified. The analysis methodology is based on the symbiosis of the neoinstitutional approach and game theory (continuous games) with the rent-oriented behavior of players. The urgency of the problems of lobbist organizations is due to the prolonged political and managerial crisis, both in Europe, the USA and in the countries of Asia. The scientific novelty of this paper is determined by the use of the neoinstitutional approach and the theory of games with the rent-oriented behavior of players as the fundamental methodological direction of the symbiosis when considering lobbist organizations as conflict resolution institutes with all the functions and rules of behavior in a political game inherent in them. The study will be based on the use of such empirical methods as analysis of documents and cases, which justifies the use of a qualitative methodology. The article is one of the first in Russian empirical practice related to the problem of lobbist organizations and, undoubtedly, will make a significant contribution to the study of the conflict logical specific nature of this socio-political institute. The article is part of the grant of the Russian Foundation for Basic Research No. 19-011-31376opn “Conflict logical audit as a system of technologies for influencing ideological youth extremism in modern Russia”.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".