Gillespie A. , Glaveanu V. , de Saint-Laurent C. , Zittoun T. , BERNAL MARCOS, MARCOS JOSÉ
No
J. Mix Methods Res.
Article
Científica
01/09/2024
001316187200001
2-s2.0-85204523119
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. © The Author(s) 2024.
data transformation; mixed analysis; multi-resolution design; qualitizing; quantitizing