Dynamics and Limits of Regulatory Privatization: Reorganizing audit oversight in Russia
Bibliographic record
Abstract
Accounting and auditing are often cited as key sites where business regulation has been privatized, globalized and neoliberalized. Yet, these sites have also undergone a legitimacy crisis in recent years, marked by a shift from self-regulation to increased public oversight. This paper investigates these developments by reference to the evolution of a public/private audit oversight regime (audit of the auditors) in Russia. We show how, in the early stages of post-Soviet reforms, old state-administered forms of financial oversight were replaced with market-oriented arrangements (peer reviews) offered by newly founded private professional accountancy associations as a service to their members. Fifteen years later, the process of regulatory privatization culminated in a reinvigoration of public authority. Our longitudinal analysis highlights the pivotal role of the state in the liberalization of governance by showing how audit oversight privatization was not only enabled by, but also provided a condition for, the strengthening of government actors. We introduce the term ‘legislative layering’ to denote the mechanism that enabled public actors to redeploy themselves in the face of the rising market logic to ensure continuity in their regulatory objectives.
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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 | 0.006 | 0.010 |
| 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 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".