coresoi is a product of the project CO.R.E.- Corruption risk indicators in emergency, financed by the EU Commission, as part of the Internal Police Security Fund (ISF-P) program.
The goal of coresoi is to provide a sandbox environment for researchers and anti-corruption analysts to interact with the indicators of corruption risk in public procurement over emergencies we’ve designed. We also offer mock data extracted from dati.anticorruzione to aid in their analysis. Our hope is that this platform will promote greater transparency in government, by helping researchers and anti-corruption analysts to make their efforts in fighting corruption more effective.
Installation
You can install the development version of coresoi from GitHub with:
# install.packages("devtools")
devtools::install_github("CORE-forge/coresoi")CORE ecosystem 🌏
coresoi is part of the project CO.R.E. - Corruption Risk indicators in Emergency, financed by the EU Commission, as part of the Internal Police Security Fund (ISF-P) program. The project presented by the Department of Political Sciences of the University of Perugia (Italy) as leader with the coordination of Prof. Gnaldi (PI) was funded for a total of 514 thousand euros. The international network involves Universitat Obierta Catalunya ( Spain ), Dublin City University ( Ireland), Oficina Antifrau de Catalunya ( Spain), Infonodes ( Italy), Transparency International ( Portugal), Villa Montesca Foundation ( Italy). CO.R.E. focuses on assessing the risk of corruption in public procurement in emergency settings from a preventive point of view. In view of achieving this goal, central to the European agenda, CO.R.E. intends to develop and validate a replicable procedure for the construction of a synthetic (or composite) indicator (CI) of the risk of corruption in public procurement in various emergency scenarios, which can be usefully employed by national anti-corruption agencies, the media and the citizens for accountability purposes.
The development of a synthetic measure of corruption risk involves several stages:
- selection of the data
- computation of elementary indicators (i.e. red flags) of corruption risk;
- choice of normalization, weighting and aggregation schemes;
- multivariate analysis for the study of the data relational structure;
- sensitivity analysis of the resulting synthetic indicator to check its robustness.
For each of these steps, coresoi provides a support to any interested user through analytical codes, users’ guides and practical examples.
Code of Conduct
Please note that the core-soi project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.