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

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2012-05-01

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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.

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10.1177/1525822X11433998

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Basurto, X, and J Speer (2012). Structuring the Calibration of Qualitative Data as Sets for Qualitative Comparative Analysis (QCA). Field Methods, 24(2). pp. 155–174. 10.1177/1525822X11433998 Retrieved from https://hdl.handle.net/10161/6739.

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Basurto

Xavier Basurto

Truman and Nellie Semans/Alex Brown & Sons Associate Professor

I am interested in the fundamental question of how groups (human and non-human) can find ways to self-organize, cooperate, and engage in successful collective action for the benefit of the common good. To do this I strive to understand how the institutions (formal and informal rules and norms) that govern social behavior, interplay with biophysical variables to shape social-ecological systems. What kind of institutions are better able to govern complex-adaptive systems? and how can societies (large and small) develop robust institutions that provide enough flexibility for collective learning and adaptation over the long-term?

My academic and professional training is based on a deep conviction that it is through integrating different disciplinary perspectives and methods that we will be able to find solutions to challenging dilemmas in natural resources management, conservation, and environmental policy. Trained as a marine biologist, I completed a M.S in natural resources studying small-scale fisheries in the Gulf of California, Mexico. Realizing the need to bring social science theories into my work on common-pool resources sustainability, I earned an MPA and a Ph.D. in Management (with a minor in cultural anthropology) from the University of Arizona and under the supervision of Edella Schlager. Following I spent two years working with Elinor Ostrom, 2009 co-winner of the Nobel Prize in Economics, at the Workshop for Political Theory and Policy Analysis of Indiana University. Methodologically, I am familiar with a variety of quantitative and qualitative approaches and formally trained to conduct Qualitative Comparative Analysis (QCA or more recently fsQCA), that allows among other things, systematic comparisons of middle range N sample sizes and address issues of multiple-causality.


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