Measuring inter-racial friendships

Different methods of measuring inter-racial contacts produce large differences in the level of the same. Experiments conducted on the 1998 General Social Survey indicate that estimates of how many people have inter-racial friends are much higher when a direct question is asked, intermediate when a three-step procedure is used, and the least when a name-generator, network approach is used. Cognitive and social desirability reasons for these effects are discussed.     

Sources of growth and cyclical stability for Nevada counties: Transfer payments and property income

The growing relative number, the improved economic well-being, and the migration of elderly retirees is not only reshaping the social and economic structure of many areas, it is also modifying both long-term and short-run patterns of economic growth. Transfer payments and property incomes, two of the most important source of elderly income, have been among the leading sources of national income growth over the past several decades. Unlike most labor-related industry sources of earnings, the level of transfer payments and property incomes received by the residents of the region is not directly dependent upon local economic activity. Consequently, as transfer payments and property incomes of elderly retirees become increasingly important sources of income and purchasing power within a region, they also can alter regional short-run cyclical patterns of income growth. This article examines the pattern of growth of transfer payments and property incomes in the context of national economic cycles, and explores the implication of those findings on metropolitan and nonmetropolitan Nevada economies.     

Traditional, Interpretive, and Reception Based Content Analyses: Improving the Ability of Content Analysis to Address Issues of Pragmatic and Theoretical Concern

This paper argues for a subtle but important shift in the way we view content analysis which allows for the introduction of two new variants on this methodology. Previously, content analysis has been seen as a method for quantifying the content of texts. This paper argues that we should view content analysis as a method for counting interpretations of content. Based on this reconceptualization, this paper suggests two new varieties of content analysis. Reception based content analysis allows researchers to quantify how different audiences will understand text. Interpretive content analysis is specially designed for latent content analysis, in which researchers go beyond quantifying the most straightforward denotative elements in a text. These new forms of content analysis are contrasted with traditional content analysis, and the appropriate conditions for their use are discussed.     

Order statistics from non-identical right-truncated Lomax random variables with applications

In this paper, we derive some recurrence relations for the single and the product moments of order statistics from n independent and non-identically distributed Lomax and right-truncated Lomax random variables. These recurrence relations are simple in nature and could be used systematically in order to compute all the single and product moments of all order statistics in a simple recursive manner. The results for order statistics from the multiple-outlier model (with a slippage of p observations) are deduced as special cases. We then apply these results by examining the robustness of censored BLUE's to the presence of multiple outliers. Received: November 30, 1998; revised version: March 8, 2000     

An experimenter’s view of the application of statistics to cloud-seeding experiments

An experimenter in the field of cloud seeding describes aspects of experiments which he would like statisticians to take into account and suggects Problems which he would like statisficians solve.     

Robustness of Risk Maps and Survey Networks to Knowledge Gaps About a New Invasive Pest

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk‐ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.     

Conference of the Australian Association of Hospital Almoners

This paper offers a rationale for the comprehensive inclusion of women's issues in social work education. The development of women's studies is traced, with particular reference to a current social work programme at the University of New South Wales. It is asserted that women's studies has something distinctive to offer the social work curriculum.     

Combinatoric classification of multivariate normal variates

Consider classifying an n × I observation vector as coming from one of two multivariate normal distributions which differ both in mean vectors and covariance matrices. A class of dis-crimination rules based upon n independent univariate discrim-inate functions is developed yielding exact misclassification probabilities when the population parameters are known. An efficient search of this class to select the procedure with minimum expected misclassification is made by employing an algorithm of the implicit enumeration type used in integer programming. The procedure is applied to the classification of male twins as either monozygotic or dizygotic.