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This article asserts that it is beneficial to formulate theories using methods specifically designed to facilitate and promote integrations. Although it is written using illustrations primarily from sociology, the discussion is relevant to other fields to whatever extent their theories may be deemed informal (i.e., presented without explicitly defined terms, distinct propositions, or logical calculi for deriving hypotheses). Constructing theories in a modular fashion makes the processes of development and explication more efficient, and the products more generally useful. Modules are semiautonomous components designed with sufficient flexibility that they can be assembled into larger combinations which are capable of generating explanations and predictions that individual modules could not manage alone. The general benefits of modularization are demonstrated for a variety of applications, and the argument is made that modularizing our theories would facilitate refinement, integration, and problem solving. Included are several illustrations in which two or more formal theories or parts of theories from the small group literature in sociology are linked in useful ways. More explicit attention to modularizing formal theories from the outset should enhance the potential for easier integrations and solutions to a broader array of substantive problems and applications.

Nearly all of sociology's top graduate training programs require their students to complete one or two courses on sociological theory. The instructors for these courses have an extraordinary opportunity to affect the perspectives and practices of future generations of scholars. This study assesses the backgrounds, attitudes, beliefs, and practices of those instructors regarding different approaches to theorizing, with particular attention paid to topics related to science and to theory construction. Sociologists who teach required theory courses in the discipline's top fifty graduate training programs were asked a series of questions pertaining to their own training and to the courses they were teaching: Attitudes toward different kinds of theorizing, perceptions of the role that theory plays in sociology and in science, and views on the nature of science. Results indicate a strong consensus on the most important classical theorists (Marx, Weber, and Durkheim). However, attitudes and practices varied widely in regard to other classical theorists, contemporary sociological theory, and the role of scientific standards in the development of sociological knowledge. The author explores some of the implications of these attitudes and practices.

The articles by Bienenstock/Bonacich and Willer/Skvoretz claim similar goals: to explore ways that game theory and network exchange theory may inform one another. Willer and Skvoretz offer a method for conceptualizing the micro-processes of network exchange theory in game theoretic terms, and conduct empirical tests of the resulting new formulation. Bienenstock and Bonacich make explicit attempts to supplant network exchange formulations with game theory, revealing what they consider to be fatal weaknesses in the former and remedies in the latter. A thread that wends through both works is the desirability of understanding thoroughly how a micro-level phenomenon— choice—and a macro-level phenomenon— network—integrate to produce phenomena that do not exist outside the confluence of the two. After a brief examination of the terminological question `To what does the label "network exchange theory" refer?', I address a series of key issues in each of the articles.

"X-Net" is a computer simulation that I developed in conjunction with Network Exchange Theory. Users of X-Net can explore the effects of different network structures, rules of exchange, and negotiators' strategies on the dynamics and outcomes of resource exchanges in social networks. This article recounts the process of X-Net's development, in addition to key substantive, theoretical, and design issues that motivated its form and content. It concludes with a discussion of the relationship between theory, simulation, and empirical tests.

We offer the first comparison between "direct" and "indirect" methods for measuring perceptions of distributive justice in reward allocations. The direct method simply asks respondents what they would consider to be a fair salary for a particular person in a given set of circumstances. In contrast, the indirect method infers fair salaries from respondents' judgments about the relative unfairness of hypothetical salaries. The particular indirect method that we will assess is a vignette survey technique pioneered by Jasso and Rossi (1977) and used in a number of more recent publications. The vignettes describe characteristics of a hypothetical employee, with the objective of deriving what respondents believe to be the just reward for that employee. Our experimental test suggests that the two methods yield incompatible results and that neither is immune to bias. The indirect method also suffers from a type of specification error that leads to untenable results. We conclude by suggesting directions for new research to gain a better understanding of these problems and, ultimately, to circumvent them.

Faculty and graduate students associated with the Center for the Study of Group Processes at the University of Iowa use computers for a variety of research-related purposes. This article describes the various uses of computers from the perspectives of three researchers: (a) the center's director, (b) an assistant professor just establishing his research program, and (c) an advanced graduate student who has overseen laboratory operations for several years.

Sociologists have begun to explore the gains for theory and research that might be achieved by artificial intelligence technology: symbolic processors, expert systems, neural networks, genetic algorithms, and classifier systems. The first major accomplishments of artificial social intelligence (ASI) have been in the realm of theory, where these techniques have inspired new theories as well as helping to render existing theories more rigorous. Two application areas for which ASI holds great promise are the sociological analysis of written texts and data retrieval from the forthcoming Global Information Infrastructure. ASI has already been applied to some kinds of statistical analysis, but how competitive it will be with more conventional techniques remains unclear. To take advantage of the opportunities offered by ASI, sociologists will have to become more computer literate and will have to reconsider the place of programming and computer science in the sociological curriculum. ASI may be a revolutionary approach with the potential to rescue sociology from the doldrums into which some observers believe it has fallen.