The Impact of Civil Society on Control of Corruption: A Comparative Study of Russia and Iran
Bibliographic record
Abstract
This paper studies the role of civil society in controlling corruption in public services in two developing countries: Russia and Iran. Research on the relationship between civil society and corruption control in these two countries is insufficient. Selecting Russia and Iran for comparison is based on similarities between them in terms of economic and political systems, and the developments of their civil societies. This paper compares the historical developments and the status of corruption and civil society in both countries; the efforts that civil society actors have made in battling corruption; and the state’s reaction to these attempts. This study covers a period of almost three decades from the collapse of the Soviet Union in 1991 to 2020. The findings of the study show that the civil societies in both countries have had limited impact on controlling corruption over the period. Although these findings do not support a prominent role for civil society in control of corruption in past, the author argues that, according to some evidence, there is a possibility of a stronger role for civil society in combatting corruption in both countries in the future.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".