Often, comparativists seek to formulate historical (or, in Nagel's 1961 terminology, "genetic") explanations of specific historical outcomes or historically defined categories of empirical phenomena. It is their particularity -- the fact that they are instances of significant events or phenomena-- that attracts the attention of the investigator. Sometimes, there is only one or two or a small handful of such instances. Various case-oriented research strategies have emerged to accommodate this interest in specific cases and specific historical chronologies. Present-day followers of Weber, for example, employ a comparative strategy centered on extensive use of ideal types and other theoretical devices to guide the interpretation of empirical cases. Others use comparative materials to conduct "parallel demonstrations of theory" or to analyze causal mechanisms across sets of comparable cases. Still others use "universalizing," "encompassing," or "variation-finding" strategies to aid comprehension of diverse historical trajectories. Most investigators who use case-oriented strategies, however, are not self-consciously methodological; that is, they do not regard the case-oriented strategies they use as formal methodologies. Nevertheless, there is substantial agreement among comparativists concerning the essential features of the case-oriented approach.

The goals of case-oriented investigation often are both historically interpretive and causally analytic. Interpretive work attempts to account for significant historical outcomes or sets of comparable outcomes or processes by piecing evidence together in a manner sensitive to historical chronology and offering limited historical generalizations which are sensitive to context. Thus, comparativists who use case-oriented strategies often want to understand or interpret specific cases because of their intrinsic value. Most, but not all, case-oriented work is also causal-analytic. This companion goal is to produce limited generalizations concerning the causes of theoretically defined categories of empirical phenomena (such as the emergence of class-based political parties) common to a set of cases.

Many empirically oriented comparativists stress the basic, underlying similarities between case-oriented comparative work and other kinds of empirical social science. They emphasize the use of empirical data on cases to decipher important causal patterns and downplay the interpretive side of comparative work. The goal of causal generalization is emphasized to create a gulf between comparative social science and highly abstract, non-empirical work that traditionally has been called interpretive (that is, work which is concerned almost exclusively with problems of meaning). There is no necessary contradiction, however, between doing empirically based causal analysis and interpreting cases historically. Both goals (causal analysis and historical interpretations defined in this work) are important; having one does not entail a denial of the other.

In Social Origins of Dictatorship and Democracy, for example. Barrington Moore interprets the process of polity modernization in seven major countries and pinpoints common historical features constituting three major paths to polity modernization. While Moore's purpose is both to interpret these cases and to pinpoint the historical origins of these different paths, the goal of causal generalization is given precedence over the goal of historical interpretation. In some investigations, however, the goal of interpretation takes precedence over the goal of causal analysis. For example, while case-oriented comparisons are very important in Bendix's work (1977, 1978), his primary goal is to interpret each case. He produces little in the way of empirical generalization because he emphasizes the particularity of each case as a representative of a distinct theoretical type. Thus, differences between the cases he selects overwhelm their similarities.

In practice, case-oriented methods often stimulate the development of new substantive theories. The theory-generative nature of case-oriented inquiry is evident even in its most basic application the use of the method of agreement to resolve a simple paradox. Characteristically, this paradox has the form: "objects A and B are different. Yet they both experienced outcome Y. What causally relevant similarities between A and B explain this common outcome?" The goal of this type of analysis is simply to identify common causes and thereby explain a common outcome. Only when A and B are very different is it difficult to identify common causes. The more A and B differ, the greater the apparent paradox and the more challenging the task of identifying the common underlying causal factors.

An excellent example of this type of simple paradox resolution is found in Marvin Harris's (1978) investigation of various "socio-cultural puzzles". For example, Harris studied specific meat taboos in several regions of the world. From a Western point of view many of these taboos seem bizarre, and traditional explanations of these practices cite religious beliefs. Harris rejects these arguments as unscientific because a different belief system is cited in the explanation of each taboo. As a substitute for particularistic explanations, Harris is able to show that in each case the emergence of these practices resulted from ecological pressures and crises. These ecological crises, in turn, are traced to tensions between the technology of food production and human reproduction. Thus, a common outcome, religiously proscribed foods, is explained in a variety of different settings with a single overarching framework emphasizing the interplay of social and ecological constraints. In the course of showing the underlying similarities among these different settings, Harris is able to dispose of particularistic, culturalist explanations of certain food taboos.

There are three basic steps in this research strategy. First, the investigator searches for underlying similarities among members of a set displaying some common outcome (or any characteristic of interest). Second, the similarities identified are shown to be causally relevant to the phenomenon of interest. And third, on the basis of the similarities identified, the investigator formulates a general explanation. In short, it is a straightforward application of the method of agreement. It is deductive because initial theoretical notions serve as guides in the examination of causally relevant similarities and differences. (Without theoretical guides, the search for similarities and differences could go on forever.) It is inductive because the investigator determines which of the theoretically relevant similarities and differences are operative by examining empirical cases. In this phase of the investigation the researcher formulates a general explanation on the basis of identified similarities. Thus, induction culminates in concept formation and the elaboration of initial theoretical ideas.

Harris makes it look simple. But the results of applications of this strategy are rarely so neat. More typically, the process of identifying underlying similarities and differences is anything but straightforward. The problem is that the mechanical identification of similarities and differences rarely provides very much in the way of raw material for producing a satisfactory resolution of the initial paradox. Obvious similarities, which may be few in number, may be causally irrelevant to the outcome of interest or may be too general to provide a satisfacbasis for foran adequate explanation. Furthermore, the possibility of identifying types of a phenomenon as a way of circumventing the absence of underlying commonalities is not very attractive if there are only two or three cases. The more challenging the paradox and the more dissimilar the cases, the less the likelihood that causally relevant commonalities can be easily identified.

Michael Burawoy, for example, uses a case-oriented strategy in his study of the organization of work incentives at two points in time in a Chicago industrial establishment. In his book Manufacturing Consent: Changes in the Labor Process Under Monopoly Capitalism (1979) he contrasts the organization of work incentives in a single factory in the 1940s and again in the 1970s. His goal is to explain how different incentive systems produce a common outcome: worker compliance with production norms. Obvious similarities are (necessarily) few. The remuneration system used in the 1940s was oriented toward actual piece rates, and a major locus of conflict was over the rate attached to each job. In the 1970s, however, a different system prevailed, and conflict centered on base earnings and fringe benefits for different jobs and on the ease with which workers could move to the higher skilled jobs. "Whereas in 1945 bargaining between management and worker over the distribution of the rewards of labor took place on the shop floor, in 1975 such bargaining had been largely transferred out of the shop and into the conference room" (Burawoy 1979:50).

These two systems of worker remuneration produced the same outcome -- worker conformity to production norms -- on virtually identical shop floors. (Despite higher productivity, relevant technological changes were few.) Thus, Burawoy explains a constant (worker compliance) with a variable (different ways of producing it on the shop floor). At a mechanical level, few commonalities were identified, for the two systems of incentives were fairly different. Yet the outcome was the same, and Burawoy produces a convincing social scientific account of how the same outcome was produced in different ways.

This example indicates that identification of underlying commonalities often does not involve a simple tabulation and analysis of common characteristics. Investigators must allow for the possibility that characteristics, which appear different (such as qualitatively different systems of incentives) have the same consequence. They are causally equivalent at a more abstract level --- at the level of the "game" that develops on the shop floor, according to Burawoy (1979:48-60) -- but not at a directly observable level. Thus, there may be an "illusory difference" between two objects that is actually an underlying common cause when considered at a more abstract level. Allowing for the possibility of causal equivalence of apparently dissimilar features severely complicates the identification of underlying commonalities.

Another type of paradox resolution that uses a parallel case-oriented strategy involves cases with different outcomes. Two cases may appear to be very similar and yet experience different outcomes. In this type of investigation, the goal is to identify the difference that is responsible for contradictory outcomes. Instead of studying the underlying similarities between relatively dissimilar objects, the investigator studies the causally decisive differences between relatively similar objects. The basic mechanics of this type of paradox resolution are parallel to the mechanics of the first type: the investigator uses theory to aid in the identification of relevant differences; the differences identified are then shown to be causally relevant to the outcome of interest; and on the basis of the differences identified the investigator formulates or refines a general explanation of the phenomenon of interest.

Examples of this research strategy in comparative social science abound. Investigators are very concerned with matching cases as much as possible as a way to establish experiment-like designs. For example, researchers often restrict their investigations to countries that are as similar on as many theoretically relevant variables as possible. This strategy allows researchers to exclude certain types of explanations or certain confounding variables categorically. Alford (1963), for example, studied only English-speaking democracies with single-member, simple-plurality electoral systems in his study of the effect of urbanization and industrialization on the relationship between social class and party support. It was necessary to control for electoral system by holding it constant because the interpretation of the relationship between social class and party support is different in electoral systems that use proportional representation. Traditionally, this strategy has been called the "most similar nations" design.

This strategy, while experiment-like, is not without problems of its own. The first strategy, sketched above, is confounded by illusory differences features which appear different but are causally equivalent at a more abstract level. The second strategy is confounded by the obverse of illusory difference "illusory commonality." The identification of causally significant differences is the key to the success of the second strategy. Yet two cases may appear to share a certain feature which the investigator might identify as a commonality (and therefore irrelevant to the explanation of differences in outcomes), when in fact these apparently common features differ dramatically in causal significance.

Illusory commonalities exist whenever two features appear similar but have different effects. For example, employment tests are used by some employers as a gating mechanism to screen out illiterate workers, regardless of the level of literacy required on the job. They are used by others to identify applicants with the greatest job-relevant skills. It would be a mistake to equate these two uses in an investigation of firms' hiring practices, even though they appear to be similar. It probably would be necessary in this investigation to contextualize the interpretation of employment testing (as a variable) by taking into account associated practices and the skill levels employers require of employees. In a low-skill context, employment testing may indicate a simple interest in excluding illiterates, who from the employer's perspective may possess other "undesirable" traits (such as minority membership). In the high-skill context, employment testing may indicate a simple interest in hiring the most qualified workers. Thus, in an investigation of hiring practices, the use of employment tests may be an illusory commonality.

Both illusory difference and its obverse, illusory commonality, interfere with the identification of underlying similarities and differences. The more general class that encompasses both illusory commonality and illusory difference is multiple conjunctural causation. What makes a certain feature, a commonality, causally relevant in one setting and not in another is the fact that its causal significance is altered by the presence of other features (that is, its effect is altered by context). Similarly, apparently different features can have the same effect depending on which other features they are associated with. Such contextualization of the causal importance of different conditions is the rule, rather than the exception, in most case-oriented studies. This is a primary justification for examining cases as wholes and for trying to decipher how different causal factors fit together. By examining differences and similarities in context it is possible to determine how different combinations of conditions have the same causal significance and how similar causal factors can operate in opposite directions.

Such contextualized causal arguments are necessary because the problem is to explain how relatively dissimilar cases experience the outcoor how relatively similar cases experience different outcomes. Thus, mechanically identifiable similarities and differences may be few, and the investigation must focus on how conditions combine in different settings to produce the same or different outcomes. The identification of patterns of multiple conjunctural causation provides a basis for specifying, at a more abstract level, the underlying similarities responsible for similar outcomes and the underlying differences responsible for different outcomes.

One of the most valuable features of the case-oriented approach is the fact that it engenders an extensive dialogue between the investigator's ideas and the data. Each case is examined as a whole, as a total situation resulting from a combination of conditions, and cases are compared with each other as wholes. This makes it possible to address causal complexes to examine the conjunctures in time and space that produce the important social changes and other phenomena, that interest social scientists and their audiences. Furthermore, case-oriented methods require that investigators suspend assumptions about the equivalence of cases and conditions. For example, it is not assumed at the outset of an investigation that all the cases are drawn from roughly the same population or that the meaning of various measurements (including presence/absence variables) are the same from one case to the next. This flexibility, which is the hallmark of the case-oriented approach, enriches the dialogue between ideas and evidence.

The case-oriented approach works well when the number of relevant cases is relatively small. The comparison of two to four positive cases with the same number of negative cases is manageable. As the number of cases and the number of relevant causal conditions increase, however, it becomes more and more difficult to use a case-oriented approach. When there are only a few cases, as is the rule in many comparative historical investigations, it is not difficult to identify similarities because the researcher usually has (or tries to establish) an intimate familiarity with relevant cases. For most of mainstream social science, however, such intimacy is rare. The typical survey study, for example, has hundreds of respondents; the typical quantitative cross-national study includes scores of countries. Not only does the difficulty of identifying commonalities increase, but the commonalities themselves become more scarce. As the number of cases increases, the likelihood that any given causally relevant characteristic will be common to the entire set decreases.

In Social Origins of Dictatorship and Democracy, one of the best examples of the case-oriented approach, for instance, Barrington Moore (1966) analyzes only eight cases. Seven of these cases are instances of successful polity modernization. Among these seven, Moore distinguishes three types: the democratic, fascist, and communist routes to the modern world. He uses the indirect method of difference to justify his assignment of these cases to the three subtypes and, at the same time, to elaborate their important similarities and differences. These seven successful cases are contrasted with an eighth, India, an apparently unsuccessful case.

While elegant, Moore's analysis is complex. He builds an intricate web of similarities and differences that is difficult to unravel. This complexity is a direct consequence of the logic of case-oriented comparative inquiry. Cases are compared as wholes with each other. As the number of cases increases, the number of possible comparisons increases geometrically. In Moore's study, which has a modest number of cases, eight, there are twenty-eight possible comparisons. A narrative that allows this many comparisons can easily get out of hand. Only a skilled comparativist can consider all the theoretically relevant similarities and differences and keep them organized. A thorough case-oriented study of twenty cases would entail almost two hundred possible comparisons.

This expanding volume of comparisons is further enlarged if the investigator considers a large number of causal conditions. Because case-oriented comparative methods are holistic, conditions are examined in combinations. As the number of relevant causal conditions increases, the number of logically possible combinations of causal conditions increases exponentially. An investigator who considers eight different causal conditions conceived in presence/absence terms, for example, might consider a maximum of 256 different combinations of these eight conditions.

While all these different combinations certainly would not exist empirically, they are relevant to speculation about the possible impact of altered circumstances (that is, they are the raw material of thought experiments).

Comparative social scientists routinely consider how the presence or absence of a certain condition in a specific case might have altered the outcome it experienced. These theoretical comparisons using empirical and hypothetical cases are similar to the holistic comparisons of empirical cases. In this sense, the number of causal conditions considered increases the number of cases to be compared because it expands the set of relevant hypothetical cases. It is not surprising, therefore, that investigators who use case-oriented methods limit their investigations to small numbers of carefully selected cases and consider specific types of causal factors (instead of all possibly relevant causes). The volume of logically possible comparisons can easily get out of control if the analysis is not restricted in this way.

These observations on the limits of case-oriented methods turn Smelser's (1976) argument about the comparative method on its head. He argues that the method of systematic comparative illustration (that is, case-oriented methods) must be used when the number of relevant cases is too small to permit the use of statistical methods. The foregoing discussion suggests that the reverse is true. Because case-oriented methods compare cases with each other and consider combinations or conjunctures of causal conditions, the potential volume of the analysis increases geometrically with the addition of a single case, and it increases exponentially with the addition of a single causal condition. Thus, it is not the number of relevant cases that limits the selection of method, as Smelser argues, but the nature of the method that limits the number of cases and the number of different causal conditions that the investigator is able to consider.

Investigators who use case-oriented methods often combine causal analysis, interpretive analysis, and concept formation in the course of their studies. Several distinctive features of case-oriented methods make this possible. First, they are designed to uncover patterns of invariance and constant association. A cross-tabulation of cause and effect is accepted as definitive only if all deviating cases are accounted for in some way. Probabilistic relationships are not accepted as demonstrations of cause. This stringent requirement forces investigators to get very close to their data and become familiar with their cases as they try to pinpoint key differences between cases. The search for invariance encourages greater specificity in causal arguments and often leads to the development of important distinctions between subtypes of social phenomena.

The second distinguishing feature follows from the first: the method is relatively insensitive to the frequency distribution of types of cases. A single case can cast doubt on a cause-effect relationship established on the basis of many observations. It does not matter how many cases are in the presence/presence and absence/absence cells of the cross-tabulation of causes and effect. If a single case exists in any of the deviating cells, the causal relationship is questioned and the investigator must account for the deviation. Thus, notions ofsamplinand sampling distributions are less relevant to this approach because it is not concerned with the relative distribution of cases with different patterns of causes and effects. More important than relative frequency is the variety of meaningful patterns of causes and effects that exist.

Third, case-oriented methods force investigators to consider their cases as whole entities. Researchers examine cases as wholes, not as collections of variables. An interest in interpreting specific cases and in pinpointing the combinations of conditions, the causal complexes, that produce specific outcomes encourages investigators to view cases as wholes. Thus, the different parts or conditions that make up a case are understood in relation to each other. They are considered together as composing a single situation. This approach contrasts sharply with how they are treated in other types of investigations. In statistical analyses of large numbers of observations, for example, relations between parts are understood only in the context of analyses of the entire population or sample. That is, relations between parts are seen as derivative of sample or population properties, not in the context of the separate wholes they form. In most statistical analyses, population or sample patterns determine how the parts of a single case are understood.

Fourth, case-oriented methods stimulate a rich dialogue between ideas and evidence. Because these methods are flexible in their approach to the evidence-- few simplifying assumptions are made-- they do not restrict or constrain the examination of evidence. They do not force investigators to view causal conditions as opponents in the struggle to explain variation. Rather, they provide a basis for examining how conditions combine in different ways and in different contexts to produce different outcomes.

Thus, case-oriented studies have unique strengths and they have limitations. The distinctiveness of the case-oriented approach is magnified when contrasted with the variable-oriented approach, the focus of the next reading assignment.

Alford, Robrt, Party and Society, Chicago, Chicago University Press, 1963.

Bendix, Reinhard, Nation-Building and Citizenship: Studies of Our Changing Social Order, Berkeley, University of California Press, 1977.

Bendix, Reinhard, Kings or People: Power and the Mandate to rule, Berkeley, University of California Press, 1978.

Harris, Marvin, Good to Eat: Riddles of Food and Culture, New York, Simon and Schuster, 1985.

Nagel, Ernest, The Structure of Science, New York, Harcourt, 1961.

Smelser, Neil, Comparative Methods in the Social Sciences. Englewood Cliffs, New Jersey, Prentice-Hall, 1976.