Quantitative Falsification for Qualitative Findings: Falsifying an Ethnographic Theory of American Public Discourse on Nuclear Waste With Text Mining in R

How can ethnographic theories that are qualitative and interpretive in nature also be scientific? This article puts forth an illustrative answer: It employs quantitative text mining methods to falsify prior findings reached largely through qualitative interpretations. The author’s earlier research innovated on core anthropological methods to offer that U.S. public discourse on radioactive waste between 1945 and 2009 may be best understood in terms of two paradigmatic waves that differ from each other in conceptualization of nuclear waste as well as in how nuclear waste relates to the broader environment and to human health. This article distills those earlier qualitative findings into a list of refutable statements that are subsequently assessed through quantitative analysis of the textual corpus of the original proxy for the ethnographic repository through employing the R statistical programming language (Version 3.4.0). As this case of quantitative analysis lends confidence on the validity of the interpretive conclusions in question, this article suggests that quantitative falsification testing may be a fit way for ethnographic findings to fulfill their scientific ambitions