Maria Isabel Espinoza, Rutgers University
Digital transformation and the rise of new technologies have increased pressure on government departments to turn towards data-driven policymaking and implementation by streamlining their data collection, analysis, and sharing practices. Implementing such evidence-based government action requires flows and articulations of data through a wide array of actors, from public servants working at different government levels to researchers and NGO workers. Past STS studies have primarily focused on the role that data articulations play in facilitating the translation of broad international policy approaches into local contexts or transforming raw data into national statistics and other kinds of actionable data. This article focuses instead on instances where data flows are truncated or obscured, and thus does not inform government interventions. As an example, I use the case of Peru’s vector control program to fight dengue and other vector-borne diseases. Based on 37 in-depth interviews and analysis of official documents, this study illustrates how data is sometimes unarticulated and even sequestered due to the precarity of data management and data sharing infrastructures and also an unsuccessful decentralization process. The decentralization of the health sector, which was part of the early 2000s neoliberal structural adjustment policies in Peru, has disrupted the capacity of the national and subnational governments to carry out large-scale health programs, such as vector control activities. It has also heightened distrust between experts working at the national and subnational levels and between these government workers and the research community, impeding data flow. These findings contribute to past work on the sociology of knowledge that notes bureaucracies and other types of organizations sometimes seek to maintain ignorance and ambiguity. They also contribute to the field of global health by showing how public health experts navigate pressures of “governing by numbers” in developing countries.
No extended abstract or paper available
Presented in Session 154. Innovations in Data Infrastructure