Bureaucratic reform and Russian transition: the puzzles of policy-making process
Bibliographic record
Abstract
Abstract During the two decades of post-Soviet transition, Russia has created a complex system of civil service and public administration. This system was first reformed in the early 1990s and then again in the early 2000s. The analysis presented here fills a gap in the existing literature concerning the dynamic of change associated with Russian civil service reform (CSR). It is argued that the process of bureaucratic modernization in Russia is undermined by the ambivalent nature of policy leadership with its financial, administrative, and technical support, and the ongoing bargain among policy advocates and policy implementers. In order to account for the outcomes reached by policy-makers, the paper presents a detailed analysis of expert interviews collected by the author among research community specialists, federal legislators, and other participants in the reform. The discussion highlights the importance of power dynamics, which resolves conflicting views of CSR among policy formulators and policy implementers. The findings, which consist of identifying necessary and sufficient conditions of the change process, have implications for studies of modern Russian politics, states in regime transition, and world-wide modernization.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.024 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".