Quality Control for Quality Computational Concepts: Wrangling with Theory and Data Wrangling as Theorizing

Abstract

Sociologists find themselves confronted with digitized data about all aspects of social life, yet this data is of indefinite quality. How may they use the process of inspecting and cleaning this data an occasion to advance social theory? We draw on Art Stinchcombe’s theory of formality to demonstrate how the craft of data wrangling can be used to assess and improve the quality of our concepts. Drawing on examples from contemporary computational social science, we show how the cognitive adequacy, communicability, and improvability of conceptual abstractions can be developed and refined in the data wrangling process. Using Stinchcombe to bring attention to the link between theorizing and the organizational and institutional systems in which it is embedded, we argue that the systems that impact the quality of our data simultaneously impact the quality of our concepts.