ICQE26

Building on the success of previous ICQEs, the Eighth International Conference on Quantitative Ethnography will bring together scholars seeking to meaningfully analyze complex processes in rich datasets from the perspective of quantitative ethnography.

The goal of ICQE is to foster a community of researchers interested in sharing methodological innovations and applied research using techniques such as Epistemic Network Analysis across increasingly diverse and interdisciplinary fields. ICQE is a space for new and established quantitative ethnographers to share ideas, resources, and inspiration.

Our venue, the International Conference Center Hiroshima (ICCH), is situated in the heart of the Peace Memorial Park—a location that serves as a global symbol of peace and resilience. As we gather to discuss the future of quantitative ethnography, there is no better place to foster international collaboration and visionary thinking. We look forward to welcoming the global research community to this world-class facility for a week of groundbreaking science and unforgettable cultural experiences.

Can ethnography be quantitative? For Takashi Otani, a qualitative research methodologist and developer of SCAT (Steps for Coding and Theorization), the term “Quantitative Ethnography” (QE) initially sounded like an oxymoron. This apparent contradiction provides the starting point for a dialogue with David Williamson Shaffer, the founder of QE.

Drawing on their distinct methodological perspectives, the speakers explore three fundamental questions: What does “quantitative” mean in QE? What role does coding play in analysis and theorization? And how are quantitative and qualitative approaches related? Their conversation moves from practical methodological questions to deeper epistemological issues concerning interpretation, transparency, and the justification of research claims. What, precisely, is quantified in QE, and for what purpose? Does QE require Epistemic Network Analysis (ENA), and what kinds of qualitative data can it examine? How do researchers’ interpretations shape analytical decisions, and how can these decisions be made transparent and open to scrutiny? In particular, the speakers consider how quantitative models and original qualitative data can inform one another, and what it means to “close the interpretive loop” while remaining open to alternative interpretations.