Behavior, Belonging, and Belief: A Theory of Ritual Practice

A new model of ritual based on Durkheim's ([1912] 1995) theory is developed. It is argued that ritual practices generate belief and belonging in participants by activating multiple social–psychological mechanisms that interactively create the characteristic outcomes of ritual. Specifically, the distinctive elements of ritual practice are shown to induce altered subjective states and effortful and/or anomalous behaviors, which are subsequently misattributed in such a way that belief and belonging are created or maintained around the focus of ritual attention. These processes are traced in detail, and the resulting model is shown to be empirically credible, comprehensive, and theoretically fertile.     

Luxembourg's Foreign Policy: Does Small Size Help or Hinder?

As a very small state, Luxembourg would not appear to qualify as an influential foreign policy actor either in Europe or the world. Yet the country's international influence has long belied its reputation as a small state. This article reviews the literature on small-state foreign policy and finds that it offers numerous contradictory conclusions. As a case study it then addresses Luxembourg in the 1990s, with particular attention to two themes: its active participation in the European Union (EU) and its policies directed at maintaining economic prosperity. The paper goes on to explain Luxembourgish foreign policy behaviour through three levels of analysis and assesses to what extent smallness is a benefit or a hindrance to Luxembourg's success in meeting its international goals.     

Dairy Farm Survival in a Metropolitan Area: Dutchess County,New York, 1984–19901

Abstract The effect of nonfarm development on dairy farm survival in New York's highly developed lower Hudson Valley is analyzed. The major hypothesis is that significant losses of dairy farms during this period are the result of urban development pressures. Contrary to this hypothesis, however, the bivariate and multivariate analyses of data from a mail survey of all commercial dairy operators in Dutchess County as of 1984 and industry survivors, exiters, and new entrants through 1990 demonstrate that nonfarm development has a negligible effect on dairy farm survival; rather, survival is significantly affected by age of operator and by family disruption. Thus, demographic and family process factors are found to be more powerful determinants of dairy farm survival in this particular metropolitan context.     

The arithmetic of growth: Methods of calculation

This is a tutorial on the relations between population data and the rates of growth that are calculated from the data. For the calculation of rates of growth, discrete and continuous compounding will be compared so that the reader can see the reasons for using the mathematics of continuous compounding, which is the mathematics of exponential growth. Some properties of exponential growth are developed. Semi-logarithmic graphs will be discussed as a device for representing the size of growing populations and for analyzing the nature of the growth. Illustrative examples will be worked out in order to emphasize applications and utility.     

Multiparameter evidence synthesis in epidemiology and medical decision-making: current approaches

Summary.  Alongside the development of meta-analysis as a tool for summarizing research literature, there is renewed interest in broader forms of quantitative synthesis that are aimed at combining evidence from different study designs or evidence on multiple parameters. These have been proposed under various headings: the confidence profile method, cross-design synthesis, hierarchical models and generalized evidence synthesis. Models that are used in health technology assessment are also referred to as representing a synthesis of evidence in a mathematical structure. Here we review alternative approaches to statistical evidence synthesis, and their implications for epidemiology and medical decision-making. The methods include hierarchical models, models informed by evidence on different functions of several parameters and models incorporating both of these features. The need to check for consistency of evidence when using these powerful methods is emphasized. We develop a rationale for evidence synthesis that is based on Bayesian decision modelling and expected value of information theory, which stresses not only the need for a lack of bias in estimates of treatment effects but also a lack of bias in assessments of uncertainty. The increasing reliance of governmental bodies like the UK National Institute for Clinical Excellence on complex evidence synthesis in decision modelling is discussed.     

Design optimization using ANOVA

This paper describes the design optimization of a robot sensor used for locating 3-D objects employing the Taguchi method in a computer simulation scenario. The location information from the sensor is to be utilized to control the movements of an industrial robot in a 'pick-and-place' or assembly operation. The Taguchi method, which is based on the Analysis-of-Variance (ANOVA) approach, is utilized to improve the performance of the sensor over a wider operating range. A review of the Taguchi method is presented along with step-by-step implementation details to identify and optimize the design parameters of the sensor. The method allows us to gauge the impact of various interactions present in the sensor system exclusively and permits us to single out those factors that have a dominant influence on the overall performance of the sensor. The investigation suggests that the Taguchi method is a more structured and efficient approach for achieving a robust design compared with the classical full factorial design approach.