Structuring the Calibration of Qualitative Data as Sets for Qualitative Comparative Analysis (QCA)

Bibliographic Data

ID2407409
AuthorsXavier Basurto (0000-0002-5321-3654, Duke University, corresponding author), Johanna Speer (0000-0003-1636-803X, Humboldt-Universität zu Berlin)
Year2012
Volume24
Issue2
Pages155-174
Publication date2012-05-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueCAM (JOURNAL)
Journal identifiersISSN: 1087-8513 • E-ISSN: 1552-3969
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/1525822x11433998
OpenAlexW2099759257
LanguageEN
Citations received54
References cited25

Most studies that apply qualitative comparative analysis (QCA) rely on macro-level data, but an increasing number of studies focus on units of analysis at the micro or meso level (i.e., households, firms, protected areas, communities, or local governments). For such studies, qualitative interview data are often the primary source of information. Yet, so far no procedure is available describing how to calibrate qualitative data as fuzzy sets. The authors propose a technique to do so and illustrate it using examples from a study of Guatemalan local governments. By spelling out the details of this important analytic step, the authors aim at contributing to the growing literature on best practice in QCA

Calibration · Data mining · Data science · Focus (optics) · Machine learning · Macro · Management science · Political science · Qualitative analysis · Qualitative comparative analysis · Qualitative property · Qualitative research · Social science · Sociology · Statistics · Structuring · Computer Science · Mathematics · Qualitative Comparative Analysis Research

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Open DOISci-HubOpen Access