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Open Government Data as an Anticorruption Intervention in Megacities of the Global South: Do Local-Level Accountability Actors Actually Use Open Data?

Civil Society
Local Government
Public Administration
Qualitative
Corruption
Policy Implementation
Big Data
Theoretical
Fabiano Angélico
Jean-Patrick Villeneuve
Università della Svizzera italiana

Abstract

Transparency and open data are regarded as means for improving governance, including control of corruption. For this reason, there has been an explosion of access to information laws and open data portals in the last 25 years. However, a crucial aspect of the interrelation between open government data and corruption control is still understudied: data use. This paper investigates the uses and barriers to the use of open government data to counter corruption. The study focuses on a megacity - Sao Paulo - the largest city in Brazil and in all South America. São Paulo is one of the pioneer members of a multilateral open government initiative (OGP Local Program). We looked at a specific dataset targeting a sensitive topic, urban land and real estate ownership. This particular data set has been made available to all actors for 6 years (2016-2022). The analysis uses various sources, including official documentation and a series of in-depth semi-structured interviews with key accountability actors. The results show that contrary to expectations, accountability organizations, from civil society and government, have not systematically used the dataset, despite its potential for unveiling illicit acts. We observed numerous barriers to data use for anticorruption purposes in a megacity, ranging from the limited quality of data and lack of resources and capacity for data interpretation to professional demotivation, institutional accountability failures and political disincentives. This finding contributes to the growing literature on the limits of the principal-agent model for anticorruption policy prescriptions. This model recommends more transparency but without acknowledging the barriers to data use in local contexts, particularly in the Global South.