Edward Brent

Characteristics of children of alcoholics: putative risk factors, substance use and abuse, and psychopathology.

A sample of 253 children of alcoholics (COAs) and 237 children of nonalcoholics (non-COAs) were compared on alcohol and drug use, psychopathology, cognitive ability, and personality. COAs reported more alcohol and drug problems, stronger alcohol expectancies, higher levels of behavioral undercontrol and neuroticism, and more psychiatric distress in relation to non-COAs. They also evidenced lower academic achievement and less verbal ability than non-COAs. COAs were given Diagnostic Interview Schedule alcohol diagnoses more frequently than non-COAs. The relation between paternal alcoholism and offspring alcohol involvement was mediated by behavioral undercontrol and alcohol expectancies. Although gender differences were found, there were few Gender X Family History interactions; the effects of family history of alcoholism were similar for men and women. When gender effects were found, they showed greater family history effects for women.

When prophecy bends: The preference–expectation link in U.S. presidential elections, 1952–1980.

A locking mechanism for effectuating the locking of individual gun barrels to a wall or gun case which includes at least one rotatable jaw which is in opposition to an opposite jaw. The opposite jaw may be either rotatable or fixed. The configuration of the jaws causes them, when locked, to envelope or encircle the gun barrel thereby locking the gun in place.

Qualitative Computing: Approaches and Issues

This paper reviews three approaches to using computers to perform qualitative analysis. These approaches are distinguished by the way they represent knowledge in the computer—as text, things, or concepts—and the operations they permit on that knowledge. These approaches are compared and the advantages and disadvantages of each are identified based on the way they perform basic tasks of qualitative research. Finally, fundamental issues and problems likely to influence qualitative computing for years to come are discussed.

Feeling the beat: intelligent coding advice from metaknowledge in qualitative research

There are few tasks in research more onerous than coding qualitative data. Ironically, the coded data in a qualitative research database themselves represent a great store of knowledge largely untapped by traditional qualitative analysis programs. By “feeling the beat” in data and by using the information that is implicit in coded cases (the metaknowledge), we can develop more intelligent qualitative analysis programs that can offer active assistance with coding, thus reducing the burden to researchers, making coding more efficient, and improving its quality. In this article, the authors examine the coding process, then show how intelligent computational strategies—case-based reasoning, natural-language generation, semantic networks, and production rules—can take advantage of the knowledge implicit in coded information in qualitative databases to help code additional data. This approach dramatically alters the relationship of data to the researcher from passive database to active agent, with important implications for both methodology and theory.

Sociology: Modeling Social Interaction With Autonomous Agents

Intelligent agents offer a promising new means for modeling social interaction. This article reviews the literature on intelligent agents, focusing on the development of agents to model various forms of social interaction. It provides a framework for understanding the variety of work on agents and how that work applies to social interaction. This framework includes a breakdown of the ways in which agents can be applied to social interaction, the various aspects of social interaction that can be modeled, and some of the broader sociological implications of using agents to model social interaction. The article concludes with a brief assessment of the promise and potential of this approach for modeling social interaction.

Assessing Research Methodology

This paper reports the development and application of a method for evaluating the methodology of social science research. In this study, 11 social scientists rated the methodology of 126 federally sponsored, social science research projects. Written documentation from each research project was divided into three packets, representing three stages of the research process: proposal, interim report, and completed research. Each project was independently rated at each of the three stages by two different reviewers, using a comprehensive methodology review instrument created for this purpose. A series of factor analyses of the ratingsfor 75 evaluative methodological features reveals a multidimensional structure underlying the evaluations. This structure appears to become more elaborate as research progresses toward completion. The implications of the structuring of methodological assessments are discussed for research funding procedures, research monitoring, the conduct of research, and the training of social scientists.

Is there a role for artificial intelligence in sociological theorizing

This article discusses the role artificial intelligence techniques can play in developing sociological theories. First, artificial intelligence is briefly introduced, and key features that distinguish this from other computing approaches are identified. Then several recent attempts to employ artificial intelligence programming strategies to assist in theory construction in sociology are described to illustrate the variety of contributions artificial intelligence can bring to sociological theorizing. Finally, some of the future prospects for artificial intelligence and sociological theorizing are discussed.

Sociology: a computational approach to sociological explanations

The capacity to explain important elements of social life is central both to the development of sociological theory and to teaching sociology. This research seeks to expand our understanding of sociological explanation through a computational approach. Explanations commonly encountered in introductory sociology texts are used to develop a typology of explanatory forms. A computational strategy that represents sociological knowledge using a combination of frames, semantic networks, and procedural rules is described. It is then demonstrated that this approach can generate the full range of these explanations for all logical combinations of conditions and for the full scope of sociological knowledge. This approach is also shown to be capable of identifying appropriate explanations, assessing the quality of explanations, and generating new insights.The capacity to explain important elements of social life is central both to the development of sociological theory and to teaching sociology. This research seeks to expand our understanding of sociological explanation through a computational approach. Explanations commonly encountered in introductory sociology texts are used to develop a typology of explanatory forms. A computational strategy that represents sociological knowledge using a combination of frames, semantic networks, and procedural rules is described. It is then demonstrated that this approach can generate the full range of these explanations for all logical combinations of conditions and for the full scope of sociological knowledge. This approach is also shown to be capable of identifying appropriate explanations, assessing the quality of explanations, and generating new insights.

Computing in sociology: promise and practice

The state of a social science discipline should be judged by the vitality of its computing subfield, which is reflected in the quality of its software. Computing progress in sociology is evident in new software for theory, data management, and instruction. Constraints including inadequate resources, problematic software, and inadequate rewards for computing contributions prohibit most sociologists from using the most innovative software. Some specific recommendations are offered for improving sociologys computing community. Keywords: sociology, microcomputing, theory, data management, instruction, computing quality, reward system.

Disambiguating verbal comments in social interaction: A computer model of meaning*

This paper describes a computer program for disambiguating the meaning of verbal acts in social interaction. The program was implemented using artificial intelligence techniques, representing utterances by frames, designing separate agents employing procedural rules to infer values of each coding dimension, and sharing information through a blackboard. The computer algorithms are discussed and illustrated with examples, then results of an empirical test of the program are reported. A training‐set of verbal interactions among health care practitioners and patients was examined to build the program, with an independent test‐set of data used to assess program performance. On a practical level, this program offers a promising approach for computer‐assisted or even automatic coding of interaction processes, reducing coding costs and improving reliability and validity. On a theoretical level, these algorithms offer a model of how individuals disambiguate the meaning of verbal comments in social interaction, pro...