Recent trends in the process of stratification

Using the 14 annual cross-sections from the General Social Survey, we specify a "basic model" of attainment and describe the year-by-year fluctuations in its parameters. The results are partially consistent with theories describing the gradual growth of universalistic patterns of stratification and mobility. Under a linear model of educational achievement, we find that the direct effects of race are weakening and the returns to class-based advantages are declining in tandem. The contours of the socioeconomic "gender gap" are also changing in important ways, with the male intercept declining at a rapid pace and the female term registering small and insignificant year-by-year gains. At the same time, the returns to experience and schooling are increasing for men, whereas the corresponding returns for women have remained stable over the 15-year period. This pattern of interaction effects implies that the size of the gender gap varies over time and across different population groups.     

Basic aspects of evolution strategies

Evolution strategies (ESs) are a special class of probabilistic, direct, global optimization methods. They are similar to genetic algorithms but work in continuous spaces and have the additional capability of self-adapting their major strategy parameters. This paper presents the most important features of ESs, namely their self-adaptation, as well as their robustness and potential for parallelization which they share with other evolutionary algorithms.Besides the early (1 + 1)-ES and its underlying theoretical results, the modern ( + )-ES and (, )-ES are presented with special emphasis on the self-adaptation of strategy parameters, a mechanism which enables the algorithm to evolve not only the object variables but also the characteristics of the probability distributions of normally distributed mutations. The self-adaptation property of the algorithm is also illustrated by an experimental example.The robustness of ESs is demonstrated for noisy fitness evaluations and by its application to discrete optimization problems, namely the travelling salesman problem (TSP).Finally, the paper concludes by summarizing existing work and general possibilities regarding the parallelization of evolution strategies and evolutionary algorithms in general.     

Ropes course training for youth in a rural setting: “At first I thought it was going to be boring ...”

Outdoor structured activities, such as Ropes Challenge Courses, are typically utilized as interventions for youth coming from urban settings. Evaluation of such programs is scanty at best. In this instance, the course experience is used as a prevention tool for high risk youth in a remote, rural setting of high unemployment, alcohol problems, and low income. The authors discuss the effectiveness of this approach, and the intended and unintended consequences for the rural community at large. The evaluation design relies on extensive qualitative methodology as well as quantitative methods to capture the unique nature of this rural project.     

Is There a Forest Transition? Deforestation,Reforestation, and Development1

Abstract Environmental social scientists have recently begun to use the term 'forest transition' to describe how forest cover changes as economic development occurs in nations. The hypothesized transition occurs as follows. An initial surge in economic activity in impoverished societies spurs deforestation, but as economic activity continues to intensify and cities grow larger, a 'turnaround' occurs, and deforestation gives way to reforestation. This paper uses cross-national data from five successive surveys of world forest resources to assess this empirical claim. A turnaround in forest cover trends does occur in a significant number of nations. The paper also evaluates two explanations for the turnaround, a wood scarcity hypothesis derived from microeconomic theory and an industrialization hypothesis linked to central place theory. It finds period specific support for the industrialization hypothesis. The paper concludes with a brief discussion of the implications of these findings for proposals to alleviate the biodiversity crisis through programs of reforestation.     

Power, Politics, and the Framing of Environmental Illness

The medical community, along with other government agencies, has created its own frame of environmental illness. This frame has been generally accepted by the American public. In this paper we discuss framing in general and the factors related to how the environmental illness frame has been constructed and maintained. We offer a brief history of the medical institution and illustrate the frame with its definitions of environmental illness. Qualitative data from a study of Oak Ridge, a contaminated community located in Tennessee, are examined to analyze the consequences of challenging the environmental illness frame. Implications for future research are discussed.     

The role of demographic and economic characteristics of twelve member states of the European Union in the diversity of state support for families

"This study is based upon an international dataset comparing state support for families in fifteen countries (of which twelve are member states of the European Union).... Using multiple regression analysis, the levels of state support are explained by the principal parameters used for setting the levels of benefit, and by the demographic and economic characteristics of the countries concerned....[Results suggest] that the economic convergence of the member states is likely to promote greater similarity in their systems of state welfare support for families." (EXCERPT)     

The NTEE classification system: tests of reliability/validity in the field of higher education

An analysis of the field of higher education reveals a surprisingly large number of classification errors within the (US) National Taxonomy of Exempt Entities database. Of the nearly 4,000 non-profit entities coded within the universe of institutions of higher education, we estimate that approximately 60 per cent were incorrectly included (Type II errors). Institutions incorrectly excluded from the higher education universe (Type I errors) represent roughly 10 per cent of the institutions coded correctly. These errors result primarily from assigning codes on the basis of the names of organisations (for example, College Park Towers is classified as a college, when it is in fact a housing complex for senior citizens) and from trying too hard to assign codes in ambiguous situations. The consequences can be significant for the users of these data, and we recommend raising bright warning flags while simultaneously enlisting the help of the entire non-profit sector in improving the classification coding process.The authors are with The Andrew W. Mellon Foundation. In addition to our colleagues on the staff of the Foundation, we wish to thank Helmut Anheier, Ted Bozovich, Harvey Dale, Virginia Hodgkinson, Stephen Noga and Christopher Toppe for helpful suggestions.