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Figure 4.1 illustrates the point (Bernard 1996). The stereotypes of qualitative and quantitative research are depicted in cells A and D, respectively. Cell A captures interpretive approaches to text, including traditions such as grounded theory (Charmaz 2014) and discourse analysis (Farnell and Graham 2015). Cell D captures the statistical analysis of numerical data, such as from closed-ended survey research. But these combinations don’t exhaust the possibilities. In cell B, the qualitative analysis of quantitative data refers to the act of extracting meaning from the results of statistical analysis or mathematical processing. All so-called quantitative research involves this interpretive act; without it, there would be little point in running a regression model or producing a scatterplot. Last, methods in cell C generally involve turning words – or images or photos or artifacts – into numbers to look for patterns. That’s the essence of classic content analysis (Krippendorff 2018). We can also place methods for cultural domain analysis like free listing and pile sorting in this cell (Dengah et al. 2021; Weller and Romney 1988).