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A recent challenge is how to mix qualitative interpretation with computational techniques to analyze big qualitative data. To this end, we propose “multi-resolution design” for mixed method analysis of the same data: qualitative analysis zooms-in to provide in-depth contextual insight and quantitative analysis zooms-out to provide measures, associations, and statistical models. The raw qualitative data is transformed between excerpts, counts, and measures; with each having unique gains and losses. Multi-resolution designs entail transforming the data back-and-forth between these data types, recursively quantitizing and qualitizing the data. Two empirical studies illustrate how multi-resolution design can support abductive inference and increase validity. This contributes to mixed methods literature a conceptualization of how mixed analysis of the same big qualitative dataset can create tightly integrated synergies.
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Alex Gillespie
Vlad Petre Glăveanu
Constance de Saint Laurent
Journal of Mixed Methods Research
London School of Economics and Political Science
University of Neuchâtel
Dublin City University
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Gillespie et al. (Mon,) studied this question.
www.synapsesocial.com/papers/68e58475b6db643587521653 — DOI: https://doi.org/10.1177/15586898241284696