Methodological Transformations in Contemporary Political Science

Flávio da Cunha Rezende


This article seeks to identify, map, and understand a set of institutions – understood as values, beliefs, and parameters – that structure the scientific knowledge in political science over the past 20 years. Its basic purpose is to map the “fundamental” values that had produced a new paradigm for academic production in the contemporary political science. The central argument of the paper is that Political Science is moving throughout a methodological transformation in which causal inference is pursued by means of several research design types, condition I named as inferential pluralism.


Metodologia; Ciência Política; Pluralismo Inferencial; Inferência Causal

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Abadie, Alberto, Alexis Diamond, and Jens Hainmuller (2012). Comparative Politics and the Synthetic Control Method. Working Paper. Mimeo.

Ahmed, Amel and Rudra Sil (2012). When Multi-Method Research Subverts Methodological Pluralism—or, Why We Still Need Single-Method Research. Perspectives on Politics, 10 (4), pp.935-53.

Aldrich, John H., James E. Alt, and Arthur Lupia (2008). “The EITM Approach: Origins and Interpretations”. In Box-Steffensmeier, Janet M., Henry E. Brady, and David Collier (eds.) The Oxford Handbook of Political Methodology. Chapter 37. pp.828-843.

Angrist, Joshua D. and Jörn-Steffen Pischkie (2009). Mostly Harmless Econometrics: An Empiricist Companion. New Jersey. Princeton University Press.

APSA (2014). Symposium: The Set-Theoretic Comparative Method: Critical Assessment and the Search for Alternatives. Qualitative & Multi-Method Research, 12(1). Organized Section for Qualitative and Multi-Method Research.

Beach, Derek and Rasmus Brun Pedersen (2013). Process-Tracing Methods: Foundations and Guidelines. Ann Arbor. University of Michigan Press.

Blyth, Mark (2006). Great Punctuations: Prediction, Randomness, and the Evolution of Comparative Political Science. American Political Science Review, 100(4). pp.493-498.

Box-Steffensmeier, Janet M., Henry E. Brady, and David Collier (2008). “Political Science Methodology”. In Box-Steffensmeier, Janet M., Henry E. Brady, and David Collier (eds.) The Oxford Handbook of Political Methodology. Chapter 1. pp.3-31.

Brady, Henry E. and David Collier (2004). Rethinking Social Inquiry: Diverse Tools, Shared Standards. New York. Rowman & Littlefield Publishers, Inc.

Brady, Henry E., Collier and Jason Seawright (2006). “Toward a Pluralistic Vision of Methodology” Political Analysis, 14(3). pp14(3):353–368.

Braumoeller, Bear F. and Gary Goertz (2000). “The Methodology of Necessary Conditions”. American Journal of Political Science, 44(3), pp.844-858.

Clarke, Kevin A. and David M. Primo. (2012). A Model Discipline: Political Science and the Logic of Representations. New York. Oxford University Press.

Collier, David (2008). Symposium: Case Selection, Case Studies, and Causal Inference. Introduction. Qualitative & Multi-Method Research. Fall. pp.2-4

Fearon, James (1991). Counterfactuals and Hypothesis Testing in Political Science. World Politics, 43(2), pp. 169-195

George, Alexander L. and Andrew Bennett (2005). Case Studies and Theory Development. Cambridge. , Massachussets. The MIT Press.

Gerber, Alan, Donald P. Green, and Edward H. Kaplan (2004). “The Illusion of Learning from Observational Research”. In Shapiro, Ian, Rogers M. Smith, and Tarek E. Masoud (eds.) (2004). Problems and Methods in the Study of Politics. New York. Cambridge University Press. pp.251-273.

Gerring, John (2004). What Is a Case Study and What Is It Good for? American Political Science Review , 98 (2) pp. 341-354.

Gerring, John (2005). Causation A Unified Framework for the Social Sciences. Journal of Theoretical Politics, 17(2). pp. 163-198.

Goertz, Gary and Harvey Starr (2002). Necessary Conditions: Theory, Methodology, and Applications. Lanham. Rowman & Littlefield Publishers, Inc.

Granato , Jim , and Frank Scioli (2004) “Puzzles, Proverbs, and Omega Matrices: The Scientific and Social Significance of Empirical Implications of Theoretical Models (EITM) ”. Perspectives on Politics, 2 (2), pp. 313 –23.

Granato, Jim, Melody Lo And M. C. Sunny Wong (2005). The Empirical Implications of Theoretical Models (EITM): A Framework for Methodological Unification. Working Paper presented at Southern Political Science Association. Mimeo.

Hess, Charlotte and Elinor Ostrom (2011). “A Framework for Analyzing the Knowledge Commons”. In Hess, Charlotte and Elinor Ostrom (eds.) Understanding Knowledge as Commons: From Theory to Practice. Cambridge, Massachussets. The MIT Press. Pp.41-81.

Imai, Kosuke, Luke Keele, Dustin Tingley, and Teppei Yamamoto. (2011) “Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies.” American Political Science Review 105 (4), pp. 765–89.

King, Gary, Robert Keohane and Sidney Verba (1995). “The Importance of Research Design in Political Science” American Political Science Review, 89(2), pp. 454-456.

King, Gary and Lee Epstein (2001). The Rules of Inference. University of Chicago Law Review, XXX (1). pp.1-93.

King, Gary, Robert O. Keohane and Sidney Verba (1994). Designing Social Inquiry: Scientific Inference in Qualitative Research. New Jersey. Princeton University Press

Krogslund, Chris, Donghyum D. Choi and Mathias Poertner (2015). Fuzzy Sets on Shaky Grounds: Parameter Sensitivity and Confirmation Bias in QCA. Political Analysis, 23, pp.23-41.

Mahoney, James (2007). Qualitative Methodology and Comparative Politics. Comparative Political Studies, 40, 122-144.

Mahoney, James (2010). After KKV: The New Methodology of Qualitative Research. World Politics, 62(1). pp.120-147.

Mahoney, James and Gerry Goertz (2012). A Tale of Two Cultures: Contrasting Quantitative and Qualitative Research in the Social Sciences. New Haven. Princeton University Press.

Mahoney, James, Erik Kimball and Kendra L. Koivu (2008). The Logic of Historical Explanation. Comparative Political Studies, 42(1). pp.114 -146.

Mahoney, James. (2000) ‘Strategies of Causal Inference in Small-N Analysis’, Sociological Methods and Research 28(4): 387–424.

Mahoney, James. (2003). “Strategies of Causal Assessment in Comparative Historical Analysis”, in J. Mahoney and D. Rueschemeyer (eds) Comparative Historical Analysis in the Social Sciences, pp. 337–72. New York: Cambridge University Press.

Manski, Charles F. (1999). Identification Problems in the Social Sciences. Cambridge. Harvard University Press.

Marsh, D. and Savigny, H. (2004) ‘Political Science as a Broad Church: The Search for a Pluralist Discipline’, Politics 24(3): 155–168.

Merriam, Charles E. (1921). The Present State of the Study of Politics. American Political Science Review, 15(2), pp.173-185.

Monroe , Burt L . (2013). “The Five Vs of Big Data Political Science: Introduction to the Virtual Issue on Big Data in Political Science ”. Political Analysis , Virtual Issue, 5.

Monroe , Burt L., Jennifer Pan, Margaret E. Roberts, Maya Sen, and Betsy Sinclair (2015). No! Formal Theory, Causal Inference, and Big Data Are Not Contradictory Trends in Political Science. American Political Science Association, PS. January, pp. 71-74.

Morgan, Stephen L. and Christopher Winship (2007). Counterfactuals and Causal Inference: Methods and Principles for Social Research. New York. Cambridge University Press.

Moses, Jonathon, Benôit, Rihoux, , and Bernhard Kittel (2005). Mapping Political Methodology: reflections on an European Perspective. European Political Science, 4. pp.55-68.

National Science Foundation (2002). Empirical Implications of Theoretical Models Report. 2002. Political Science Program, Directorate of Social, Behavioral, and Economic Sciences. Arlington, Va.

Norris, Pipa. (1997) ‘Towards a More Cosmopolitan Political Science?’ European Journal of Political Research, 31(1–2): 17–34.

Przeworski, Adam (2007). “Is The Science of Comparative Politics Possible?”. In Boix, Carles and Susan Stokes (orgs.). Oxford Handbook of Comparative Politics. New York. Cambridge University Press. pp.147-171.

Ragin, Charles C. (1987). The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies. Berkeley. University of California Press.

Ragin, Charles C. (2000). Fuzzy-Set Social Science. Chicago. The University of Chicago Press.

Rezende, Flávio da Cunha (2010). Analytical Challenges for Neoinstitutional Theories of Change in Comparative Political Science. Brazilian Political Science Review, vol 3(2). pp.98-126.

Rezende, Flávio da Cunha (2011). “A Nova Metodologia Qualitativa” e as Condições Essenciais de Demarcação entre Desenhos de Pesquisa na Ciência Política Comparada. Revista

Política Hoje, vol 20(1), pp.218-252.

Rezende, Flávio da Cunha (2011). Razões emergentes para a validade dos estudos de caso na ciência política comparada. Revista Brasileira de Ciência Política, 6. pp. 297-337.

Rezende, Flávio da Cunha (2015). Modelos de Causação e o Pluralismo Inferencial em Ciência Política. Working Paper #1. Núcleo de Epistemologia e Método Comparado. Recife. Universidade Federal de Pernambuco. Departamento de Ciência Política. Mimeo.

Rihoux, Benoit and Charles C. Ragin (2009). Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and Related Techniques. Applied Social Resarch Methods Series, vol 51. Thousand Oaks, California. SAGE Publications.

Rohlfing, Ingo (2012). Case Studies and Causal Inference: an integrative framework. New York. Palgrave MacMillan. ECPR Research Methods Series.

Sekhon, Jasjeet S (2009). “Opiates for the Matches: Matching Methods for Causal Inference.” Annual Review of Political Science 12(1), pp.487–508.

Schneider, Carsten Q. and Claudius Wageman (2012). Set-Theoretical Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. New York. Cambridge University Press.

Shapiro, Ian (2002). Problems, Methods, and Theories in the Study of Politics, or What´s Wrong with Political Science and What to do About it. Political Theory, vol 30(4). pp. 588- 611.

Weller, Nicholas and Jeb Barnes (2014). Finding Pathways: Mixed-Method Research for Studying Causal Mechanisms. New York. Cambridge University Press.


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