The Use of Empiricist and Narrative Methods in Comparative Social Science Research: Lessons and Insights for Third World Studies and Research

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The main objective of this paper is to make a critical assessment from the perspective of Third World studies of the methodology used for data collection and analysis in comparative macro-social science research within the framework of broad ontological and epistemological debates in the social sciences in general, and sociology in particular. The paper begins with a general discussion of the empiricist method of scientific enquiry and explanation, which in my assessment is the hegemonic approach to knowledge claims and validation in contemporary social science. The general strategy and foundation of knowledge claims of the empiricist method is briefly reviewed, with the basic assumptions of the method highlighted. That is followed by an analysis of the efforts made to ameliorate the problems associated with the application of statistical techniques of explanation and reasoning in comparative macro-social science research. I then discuss an alternative epistemological perspective to empiricism. I argue that the use of narrative as a method of producing and validating knowledge claims in comparative-historical studies in the social sciences could be theoretically grounded on a social realist ontological perspective, which underscores how time, space, and the complexity of social reality limits the validity of universal law-like generalizations. I review how macro-international processes are integrated into historical-comparative research as reflected in the works of Theda Skocpol, Charles Tilly and Immanuel Wallerstein. The limitations of the research strategies used by these scholars were identified by Philip McMichael who suggests an alternative method of incorporated comparison on a world historical scale. The paper concludes by discussing methodological lessons and insights from the discussion and analysis that are relevant for Third World studies and research.

It is pertinent to justify why ontological and epistemological debates in the social sciences are critically discussed in this paper. Critical reflection leads me to conclude that, in general, many courses in data collection techniques and analysis are silent on the deeper ontological and epistemological assumptions underpinning the use of such techniques and on their implications for the validity of knowledge claims produced by the use of such techniques. One consequence of this pedagogic orientation in methodology courses is that people use such techniques without reflecting on the ontological and epistemological assumptions and limitations underlying the techniques. To avoid the pitfalls characterizing other people's work, I argue that any technique used for data collection and analysis is based on certain fundamental ontological and epistemological assumptions. Unless one consciously acknowledges this relationship, one easily falls into the trap of treating techniques of data collection and analysis as existing sui generis (i.e., having an independent status of their own). Awareness of the epistemological assumptions of the techniques one uses results in both a recognition of the limitations inherently imposed on the validity of our knowledge claims and the need to be modest in making such claims.

By making a critical review of empiricist ontology, epistemology, and data collection method and analysis, I am not suggesting that such a method does not generate useful and valid knowledge. Rather, the aim is to strongly assert that when data collection and analysis techniques are treated as existing sui generis, they may result in wild knowledge claims that, on critical evaluation, cannot be thoroughly justified. Similarly, when one uses the narrative technique of data collection and analysis without being conscious of its ontological and epistemological assumptions and limitations, it can result in claims that cannot be justified on close scrutiny. I begin by examining the general strategy and foundations of empiricist knowledge claims. …


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