Italy's New Anti-Corruption Law: Factors that Affect Regional Implementation
Bibliographic record
Abstract
Corruption is a central cause of economic, financial, and political risk and instability; depreciated social capital and trust; democratic deficit; and violence and terrorism.It is thus no surprise that as regionalization and the integration of global markets has intensified, the fight against corruption has become an important part of the global policy agenda.This thesis investigates Italy's new Anti-Corruption Law (Legge n. 190/2012)-a law that was passed by Mario Monti's technocratic government in 2012, as part of a series of structural reforms designed to stabilize the Italian economy.This thesis looks at the Anti-Corruption Law from a regional lens.By speaking to Italian academics, jurists, politically-engaged citizens, regional anti-corruption officials, and Transparency International Italia, this thesis evaluates the implementation of the Anti-Corruption Law in two regions and identifies factors that affect its implementation at the regional level.I began my work on Italian corruption because of personal testimonies of injustice.I wanted to make a positive contribution to Italy's political reforms, but I had no idea how challenging this research project would truly be.The subject of this thesis was the lens with which I viewed my time in Italy.This is a very negative filter with which to see the world.As a result, while searching for examples of impediments to anti-corruption reform in Italy, I also became very pessimistic and jaded, and I am very thankful to all the friends and family who stuck by me during this trying time.I owe a great deal to my parents, sisters, and my close friends, especially Felicia Gabriele, Pinar Cil, and Denis Chrissikos, who graciously provided advice and editorial suggestions.I was very fortunate to have a research
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".