The Social Architecture of Integrity: Corruption Proofing of Legislation as a Socio-Legal Reform Capable of Building Public Trust
Bibliographic record
Abstract
In democratic systems, public trust is increasingly undermined when law-making is perceived as susceptible to undue influence from corrupt or criminal actors. This paper explores Corruption proofing of legislation (CPL) as more than a procedural tool, conceptualising it as a socio-legal reform with implications for institutional legitimacy and public trust. Drawing on institutional theory, the study applies a qualitative comparative policy analysis of CPL designs in Moldova, Lithuania, and Albania. The findings identify two contrasting institutional approaches: an external model relying on independent oversight bodies (Moldova and Lithuania) and an internal model embedded within parliamentary procedures (Albania). While both seek to reduce corruption risks in legislation, the analysis demonstrates that institutional design plays a decisive role in fostering public trust. Independent CPL mechanisms appear better positioned to enhance trust by ensuring impartial scrutiny and reinforcing transparency and accountability. Ultimately, the paper argues that CPL’s broader societal significance lies in its ability to reshape formal rules and informal normal of law-making, strengthening democratic resilience against state capture.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.055 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".