著者

山本 吉宣

出版者

日本政治学会

雑誌

年報政治学 (ISSN:05494192)

巻号頁・発行日

vol.27, pp.203-226,en9, 1977-03-31 (Released:2009-12-21)

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The aim of this paper is: (a) to review briefly the present stage of mathematical and quantitative political science; (b) to examine new directions for its future development; and (c) to discuss some caveats regarding the relevance of mathematical and quantitative political science and its proper institutional function.Mathematical political science is one of the ways in which we develop models regarding political phenomena and examine the extent to which they represent the real world. A major characteristic of such models is the use of mathematics, statistics, and symbolic logic. Given this general definition of mathematical political science, the field is, and has become, very diversified in terms of its aims, methods, and substantive problems. However, we can delineate two salient traditions in mathematical and quantitative political science. One may be called a “causal model” approach. The other is based on the use of “rational actor models.”In the causal model tradition, political phenomena are analyzed in terms of cause-effect relationships between variables. These relationships are usually represented by mathematical functions (equations). Mathematical equations in this kind of analysis (a) are used to deduce other propositions regarding political behavior at varied levels of aggregation, and/or (b) are examined against data, and through statistical techniques, to determine the extent to which they represent the referent world. Furthermore, simulation models can be utilized in such a way that logical consequences are obtained from a set of empirically tested propositions.Even though causal models are sometimes built implicitly on the assumption that actors, such as voters, are rational, we can single out a set of models that are different from causal models and which are directly built on the rationality assumption about political actors. In rational actor models, just as in causal models, the aims, styles and substantive problems are quite varied. While they are utilized to examine such normative problems as comparative study of decision rules which transform individual preferences into collective choice, many models have been constructed in order to represent and explain real political phenomena such as voting behavior, alliance maintenance in international politics, etc.Given the diversity of mathematical and quantitative political science, it is most difficult to set up fundamental dimensions by which we can satisfy the requirements of assessing its general appropriateness to the analysis of political phenomena and of forecasting its future development. However, let us propose two dimensions which may satisfy these two requirements. One dimension ranges from a mechanistic view of political phenomena to the view in which politics is considered as adaptive, an organized complexity. The other dimension is an idiographic-generalization continuum. Admitting that we need simple models in analyzing political phenomena at least at the elementary stage, it seems apparent that contemporary mathematical and quantitative political science, and methods and models thereof, tend to adopt a mechanistic, rather than an adaptive view, and intend to be general rather than idiographic. If politics is collective adaptation by human beings to both internal and external environments, a mechanistic view and models representing such a view, though not irrelevant, must be considered to be short of giving us a full understanding of political phenomena. If human beings adjust their objectives and change their purposes in responding to internal and external changes, idiographic approaches may be more important than implicitly assumed among many mathematical and quantitative political researchers.