Coppedge

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The City University of New York

Thickening Thin Concepts and Theories: Combining Large N and Small in Comparative Politics Author(s): Michael Coppedge Source: Comparative Politics, Vol. 31, No. 4 (Jul., 1999), pp. 465-476 Published by: Ph.D. Program in Political Science of the City University of New York Stable URL: http://www.jstor.org/stable/422240 . Accessed: 16/03/2011 21:00
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ResearchNote

ThickeningThin Concepts andTheories
Politics CombiningLargeN and Small in Comparative
Michael Coppedge

In recent controversiesabout comparative politics, it often seems as though there are only two approaches:the systematic logical deductionof universalistictheory and the more traditionalcase studies and small-N comparisonsleading more inductively to middle range theory.1The purpose of this article is to situate large-N quantitative analysis in this controversy.Quantitativeanalysis has its weaknesses, but they could be counterbalancedby some real strengths in small-N analysis. And quantitative analysis hascertainmethodologicaladvantagesthat help compensatefor some of the weaknesses of small-N analysis. On the one hand,small-N analysis tends to develop "thick"(complex or multidimensional)concepts and theories that are well-suited for descriptionand for making inferencesabout simple causationon a small scale or in a few cases, but thick concepts and theories are unwieldy in generalizingor rigorously testing complexhypotheses. On the other hand, quantitativeanalysis is justifiably criticized for its "thin"(reductionistor simplistic) concepts and theories, but it is the best method available for testing generalizations, especially generalizations about complex causal relationships. Quantitativeanalysis has hardlybegun to exploit its full potential in assimilating complex concepts and testing complex theories, largelydue to data limitations. In orderto realize its potential, scholarsneed to answertwo key questions that arise at the intersectionof small-N and quantitativeanalysis. Can thick concepts be translated into the thin format of quantitativedata?And can the nuanced,conditional,complex, and contextualizedhypotheses of small-N analysis be translatedinto quantitative models? I argue that the answertoboth questions is yes in principle, but that in orderto make these approachescomplementaryin practicewe must collect different dataand more dataand do it more systematicallyand rigorously. A Perspective on Methods In debates about the merits of differentapproachesit is healthy to bear in mind that all contain gaping methodologicalholes. Social scientists never prove anything,not even with our most...
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