This contribution is focused on the theme of building knowledge from datasets of public administrations and will concentrate, specifically, on risk and preventative measures of corruption, which will be discussed with reference to the rationale behind them, the objectives they allow us to gain, and their advantages and limitations compared to other measures of corruption repression and prevention. The final part will be devoted to the way preventative measures of corruption are accounted for in the Italian judicial system and, in particular, to a special case of such indicators, the so-called administrative anti-corruption efforts indicators. Overall, the contribution is organised in five sections. I will start with a proposal for a new classification of measures of corruption, which leaves behind the traditional reference to objective/subjective indicators and recommends a new criterion of classification based solely on the object of measurement. In the second part, I will synthetize the principal methodological limitations and critical issues related to the construction and use of traditional corruption measures. This second section is instrumental to introducing the third section, devoted to risk and preventative measures of corruption, whose development has been solicited also by the acknowledgement of the limits of existing corruption measures. The fourth section concentrates on a special case of risk and preventative measures of corruption, that is, administrative anti-corruption efforts indicators, which represent a distinctive mark of the Italian legislation on corruption. The contribution will end with a discussion section where it will be stressed, on one side, the need for data of good-quality to support national administrative agencies in their decision processes and, on the other side, the concurrence of a number of difficulties the Italian administrative system undergoes playing as obstacles to such a key objective.

BUILDING KNOWLEDGE FROM DATASETS OF PUBLIC ADMINISTRATIONS

michela gnaldi
2019-01-01

Abstract

This contribution is focused on the theme of building knowledge from datasets of public administrations and will concentrate, specifically, on risk and preventative measures of corruption, which will be discussed with reference to the rationale behind them, the objectives they allow us to gain, and their advantages and limitations compared to other measures of corruption repression and prevention. The final part will be devoted to the way preventative measures of corruption are accounted for in the Italian judicial system and, in particular, to a special case of such indicators, the so-called administrative anti-corruption efforts indicators. Overall, the contribution is organised in five sections. I will start with a proposal for a new classification of measures of corruption, which leaves behind the traditional reference to objective/subjective indicators and recommends a new criterion of classification based solely on the object of measurement. In the second part, I will synthetize the principal methodological limitations and critical issues related to the construction and use of traditional corruption measures. This second section is instrumental to introducing the third section, devoted to risk and preventative measures of corruption, whose development has been solicited also by the acknowledgement of the limits of existing corruption measures. The fourth section concentrates on a special case of risk and preventative measures of corruption, that is, administrative anti-corruption efforts indicators, which represent a distinctive mark of the Italian legislation on corruption. The contribution will end with a discussion section where it will be stressed, on one side, the need for data of good-quality to support national administrative agencies in their decision processes and, on the other side, the concurrence of a number of difficulties the Italian administrative system undergoes playing as obstacles to such a key objective.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1460468
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