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Aspects of Theory Evaluation

Published online by Cambridge University Press:  27 January 2009

Lawrence V. Grant
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Extract

Mathematical languages and computer algorithms are becoming important modes of analysis for theory evaluation in political science. Typically, the process involves (1) translating the major theoretical relationships into a ‘formal’ language for the logical analysis of internal consistency, or, (2) empirically interpreting the formal language in order to make specific predictions, which, in turn, allow evaluation of external consistency with theoretically significant real world phenomena. In this paper I wish to discuss, first, some basic concepts and, second, some aspects of the technology and methodology of these modes of theory evaluation.

Type
Articles
Information
British Journal of Political Science , Volume 3 , Issue 1 , January 1973 , pp. 99 - 111
Copyright
Copyright © Cambridge University Press 1973

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References

1 Brodbeck, May, ‘Models, Meanings and Theories’, in Brodbeck, , ed., Readings in the Philosophy of the Social Sciences (New York: Macmillan, 1968), pp. 579ff.Google Scholar, and Kaplan, Abraham, The Conduct of Inquiry (San Francisco: Chandler, 1964), pp. 258–91.Google Scholar

2 We might also note that saying ‘B behaves like A’ can refer to the situation in which B and A are the same things, except that A occurs in a natural setting and B occurs in an artificial setting. In this case we would say that A is the model for experiments on B.

3 The terms ‘syntactic’, ‘semantic’ and ‘pragmatic’ are intended to follow the usage of Morris, Charles W., Foundations of the Theory of Signs, in Neurath, Otto, ed., International Encyclopedia of Unified Science, Vol. I, No. 2 (Chicago: University of Chicago Press, 1938).Google Scholar

4 This problem is raised again, below, in the discussion of internal validity.

5 This argument should not be taken to infer that models are logically prior to empirical theories. Indeed, in important cases – if not all – the empirical theory is the stimulus for the model.

6 There is at least one clear cut example of a computer simulation: in some cases it is useful to make a computer behave like some other kind of computer whose principles of operation are significantly different. By writing a ‘simulator program’ for one computer B, based upon the principles of operation of another computer A, it is possible to ‘debug’ programs, written to be run on computer A, by running them on computer B.

7 Another sense of saying that B simulates or behaves like A is one in which we say that we are studying B, which behaves ‘in the same manner as A’. This suggests that we are studying something other than the empirical phenomenon in which our research interest lies. Therefore, we should distinguish between experimental and simulation research. One significant difference here is that while both experiments and simulations ‘operate’ on empirical phenomena, experiments deal directly with the object(s) under investigation and simulations deal with phenomena other than those which are the actual objects of investigation. In terms of outward appearances the kind of operations we perform in experimental research are the same as those we perform in simulation research; and, in form, they are. However, the inferences we are permitted to draw from these operations are quite different. The differences result from certain key assumptions, and differences in purpose. If we perform experiments on a group of men, our goal is to make, first, inferences about the behavior of the specific group of men. If our experiments are well designed, we may draw further inferences to the behavior of all men. However, in simulation research our goal in the operations on small human groups may be in drawing inferences about the behavior of nations or states. The point is, simulation research makes at least one assumption beyond that of a well designed experiment; namely, besides assuming that the experimental group behaves like men ‘in general’ we also assume that men ‘in general’ behave like nations. (Or, better, that role taking in small groups is essentially representative of role playing on the part of, say, decision-makers for nation states.) The usefulness of our simulation research depends completely on our confidence in this further assumption. If we lack confidence in this assumption, we are necessarily confused with respect to the inferences we can legitimately make on the basis of simulation results. The only way in which we may gain confidence that this assumption is justified is to have a sound theory descriptive of the laws which govern the behavior of the object under investigation.

8 Bauer, Raymond A., Nine Soviet Portraits (Cambridge, Mass.: MIT Press, 1955), pp. 65–70.Google Scholar

9 That is, what is the pragmatic effect of such a representation?

10 An extensive discussion of the problems encountered here is covered quite thoroughly in Hermann, Charles F., ‘Validation Problems in Games and Simulations with Special Reference to Models of International Polities’, Behavioral Science, XII (1967), 216–31.CrossRefGoogle Scholar

11 L. V. Grant, ‘Specialization as a Strategy for Legislative Decision-Making’, Midwest Journal of Political Science (forthcoming).

12 On this see especially Coombs, Clyde, A Theory of Data (New York: Wiley, 1964), Chap. 1.Google Scholar

13 Luce, R. Duncan and Raiffa, Howard, Games and Decisions (New York: Wiley, 1957), pp. 151–2.Google Scholar

14 A specific example of this may be found in Grant, L. V., Decision-Making in the United States House of Representatives: A Computer Simulation (unpublished Ph.D. Dissertation, University of Illinois, 1970), pp. 66–7.Google Scholar

15 Kessel, John, ‘A Game Theory Analysis of Campaign Strategy’, in Jennings, M. K. and Zeigler, H., eds., The Electoral Process (Englewood Cliffs, N.J.: Prentice-Hall, 1966), pp. 290–304.Google Scholar

16 See, for example, Pool, Abelson, and Popkin, , Candidates, Issues and Strategies: A Computer Simulation of the 1960 and 1964 Presidential Elections (Cambridge, Mass.: MIT Press, 1964)Google Scholar and Cherryholmes, C. H. and Shapiro, Michael J., Representatives and Roll-Calls: A Computer Simulation of Voting in the Eighty-Eighth Congress (Indianapolis: Bobbs-Merrill, 1969).Google Scholar

17 Shapiro, Michael J., ‘The House and the Federal Role: A Computer Simulation of Roll-Call Voting’, American Political Science Review, LXII (1968), 494–517, p. 497.CrossRefGoogle Scholar

18 Grant, ‘Specialization as a Strategy for Legislative Decision-Making’.

19 Coombs, , A Theory of Data, p. 5.Google Scholar

20 It should be obvious that the stimulus for this work is Campbell, Donald T. and Stanley, J. C., ‘Experimental and Quasi-experimental Designs for Research on Teaching’, in Gage, N. L., ed., Handbook of Research on Teaching (Chicago: Rand McNally and Company, 1963).Google Scholar