Ontological overflows and the politics of absence: Zika, disease surveillance, and mosquitos
Journal article, 2024

In STS, there has long existed an unease about the analysis of powerful actors and dominant technoscientific narratives. A core concern for the field has been how particular objects, phenomena, and people are excluded from technoscientific realities. However, a key problem in dealing with exclusion in STS is that our methods call us to ‘follow the actors,’ which often leads to reifying our interlocutors’ matters of concern. This paper proposes an analytical strategy that turns our analytical attention to the actors’ work rendering things absent—a strategy of analyzing ontological overflows. The aim of this analytical move is to shift focus from construction to de-construction and to highlight the importance of processes of exclusion. By exploring the actors’ making of the absence of Zika—and by extension, the construction of the absence of various technoscientific phenomena—an analytical strategy is outlined that allows us to attend to the overflows of technoscience. Four types of overflows are analyzed: conglomeration, exclusion, scarcity, and indeterminacy, each illustrating how the making of absences shapes technoscientific objects. For instance, the decision of what counts as a thing, the handling of absent data, and the translation of computational uncertainties into absence of prediction. This analytical strategy highlights where there exist spaces for power and choice—where choices can be made, by whom, and by what means. By analyzing the making of absence, we can explore how objects, phenomena, and people are marginalized or rendered absent in technoscientific processes.

exclusion

Absence

pandemic

algorithms

actor-network theory

Author

Francis Lee

Chalmers, Technology Management and Economics, Science, Technology and Society

Science as Culture

0950-5431 (ISSN) 14701189 (eISSN)

Vol. 33 3 417-442

Subject Categories

Philosophy

Social Sciences Interdisciplinary

Public Health, Global Health, Social Medicine and Epidemiology

DOI

10.1080/09505431.2023.2291046

More information

Latest update

9/11/2024