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

dc.contributor.author

Basurto, X

dc.contributor.author

Speer, J

dc.date.accessioned

2013-04-23T17:30:36Z

dc.date.issued

2012-05-01

dc.description.abstract

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. © The Author(s) 2012.

dc.identifier.eissn

1552-3969

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1525-822X

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https://hdl.handle.net/10161/6739

dc.publisher

SAGE Publications

dc.relation.ispartof

Field Methods

dc.relation.isversionof

10.1177/1525822X11433998

dc.title

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

dc.type

Journal article

duke.contributor.orcid

Basurto, X|0000-0002-5321-3654

pubs.begin-page

155

pubs.end-page

174

pubs.issue

2

pubs.organisational-group

Duke

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Marine Science and Conservation

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Nicholas School of the Environment

pubs.publication-status

Published

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24

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