Qualitative Methods in the Digital Era: How computation entangles fieldwork?

• In Event: The Promises and Pitfalls of New Technologies for Qualitative Research

Abstract

Scholars writing about the interface between qualitative and computational methods have rightly focused on machine learning. But computation can also change qualitative fieldwork in quieter ways, through scrapping, parsing, optical character recognition, archiving, and zooming. This paper situates computational methods within a wider digital era and argues that they entangle fieldwork spatially (by increasing its geographical reach), temporally (by accelerating research), and epistemically (by influencing what we can now). I show these kinds of entanglement by drawing on my own comparative-historical study of Brazil’s decarbonization capacities, which was conduct within a Ph.D. structured by COVID-19 and comparing to state-building research from three decades ago. Before the lockdown, fieldwork relied on direct observation and interviews with environmental fieldworkers and policymakers. During lockdown, computation provided continuity: web scraping, archival digitization, and machine learning substituted travel and extended the field in time and space. After restrictions eased, these computational results were reintroduced into interviews through visualizations that prompted important findings but also highlighted blind spots.

Author

• Livio Silva Silva-Muller, Harvard University