Adolescent Socialization in Rural Appalachia: The Perspectives of Teens,Parents, and Significant Adults

ABSTRACT

The purpose of this qualitative study was to explore the social networks of Appalachian adolescents to understand socialization strategies and goals. A total of 46 interviews were conducted with five families (mothers, fathers, and adolescents) and 11 socialization agents the families identified as exerting significant influence in the lives of the adolescents. Interviews were transcribed and then analyzed using principles of grounded theory. Five themes developed from the interviews: the importance of community to the socialization process, adult involvement and support, adolescent monitoring, teaching respect and responsibility, and adolescent autonomy. Results suggest the need for in-depth investigation of adolescent development within a variety of cultural and social contexts to more fully understand these processes.     

Dialectic of information? A response to Taylor

This paper is a response to Paul Taylor's review article of the book Critique of Information. The book's main thesis is that critique in the information age must be immanent critique. Taylor reproaches this for neglecting the necessity of a transcendental for critique. The response accepts this criticism. However, it rejects Taylor's aporetic notion of critique. Instead, a dialectical notion of critique is proposed. Like all dialectics this informational dialectic is one of materiality and idea. The major difference in the information age, however, is that there is a tendency for the material and the ideal to fuse in information itself. Thus the critique of information, it is argued, is a sort of immanent dialectic. This notion of critique is illustrated with reference to media art and metadata. Throughout there is an engagement with Taylor of the political implications of such critique.     

Neural Networks: A New Tool for Predicting Thrift Failures*

A neural network model that processes input data consisting of financial ratios is developed to predict the financial health of thrift institutions. The network's ability to discriminate between healthy and failed institutions is compared to a traditional statistical model. The differences and similarities in the two modelling approaches are discussed. The neural network, which uses the same financial data, requires fewer assumptions, achieves a higher degree of prediction accuracy, and is more robust.