Case Studies and Theory Development in the Social Sciences - Alexander L. George [86]
Various suggestions have been made for finding some way to deal with imperfect controlled comparison or to accept that it is inevitable. Smelser, for example, calls attention to “the method of heuristic assumption.” This is a “crude but widely employed method of transforming potentially operative/independent variables into parameters,” a method that has on occasion proven helpful in a variety of investigations.326 Arend Lijphart, while acknowledging that it is difficult to find cases that are comparable enough and that one seldom can find cases similar in every respect but one, believes that “these objections are founded on a too exacting scientific standard” and that useful research can be accomplished by studies that approximate the standard as closely as possible.327
Other writers believe that the quest for controlled comparison should be abandoned in favor of a quite different approach. Adam Przeworski and Henry Teune distinguish between a “most similar” design (the closely matched case of controlled comparison) and a “most different” research design. The former, they argue, runs into serious difficulties by failing to eliminate rival explanations. A most different design, in contrast, deliberately seeks cases of a particular phenomenon that differ as much as possible, since the research objective is to find similar processes or outcomes in diverse cases. For example, if teenagers are rebellious in both modern Western societies and tribal societies, then it may be their developmental stage, and not their societies or their parents’ child-rearing techniques, accounts for their rebelliousness.
One source of semantic confusion here is that the most similar design parallels the logic of Mill’s method of difference, while the most different design corresponds with Mill’s method of agreement. (Mill’s terms come from a comparison of the dependent variables, while Przeworski and Teune focus on comparison of the independent variables.) Here again, as Mill recognized, left-out variables can weaken such an inference; however, process-tracing provides an additional source of evidence for affirming or discrediting such inferences. Przeworski has suggested that the utility of the “most different” design approach has contributed to the considerable success of some of the literature on democratization, such as the works of Guillermo O’Donnell, Philippe Schmitter, and Laurence Whitehead. These analysts, Przeworski maintains, were forced to distill from highly diverse cases the set of common factors that possessed the greatest explanatory power.328
We have discussed in some detail the difficulty of implementing the solution offered by Lijphart and other scholars to the problem of “too many variables, too few cases”—namely, to find comparable cases so closely matched that they provide the functional equivalent of an experiment. However, while it is generally recognized that history seldom provides the investigator with cases that achieve the necessary “control,” there are rare exceptions.329 More frequently available are the aforemen-tioned “most similar” and “least similar” methods and several others to which we now turn.
THE “BEFORE-AFTER” RESEARCH DESIGN
Instead of trying to find two different cases that are comparable in all ways but one, the investigator may be able to achieve “control” by dividing a single longitudinal case into two sub-cases.330 In this connection, David Collier calls attention to the classic study by Donald Campbell and Julian Stanley in which they noted that the logic of experimental design can be approximated in “quasi-experiments.”331 They had reference to observational studies of a phenomenon occurring in a natural setting in which an event or a choice occurs at some point in time, creating the approximation of an experimental intervention. This permits the investigator to identify a “before-after” configuration within the sequential development of a longitudinal