Reasoning With Partial Knowledge

We investigate how sociological argumentation differs from classical first–order logic. We focus on theories about age dependence of organizational mortality. The overall pattern of argument does not comply with the classical monotonicity principle: Adding premises overturns conclusions in an argument. The cause of nonmonotonicity is the need to derive conclusions from partial knowledge. We identify metaprinciples that appear to guide the observed sociological argumentation patterns, and we formalize a semantics to represent them. This semantics yields a new kind of logical consequence relation. We demonstrate that this new logic can reproduce the results of informal sociological theorizing and lead to new insights. It allows us to unify existing theory fragments, and it paves the way toward a complete classical theory.     

Spiritual Gatekeepers: Time and the Rite of Christian Initiation of Adults

This article addresses the process of initiation into the Catholic Church by analyzing in‐depth interviews with parish‐based professional initiation coordinators. The formal title given to this process of initiation by the Church since Vatican II is the Rite of Christian Initiation of Adults (RCIA). Since the RCIA's promulgation, the Church has hired a host of lay and religious professionals to coordinate its implementation at the parish level. Our analysis focuses on the temporal sequencing and the problem of duration of initiation. The data show that both city and suburban coordinators adapted the Church's mandated length of time for initiation in different ways as they negotiated covenantal and contractual social relations among RCIA participants.     

The 10% Flat Tax: Tithing and the Definition of Income

Developing a fair and widely accepted income definition presents one of the greatest challenges to tax reform. To arrive at a definition separate from the federal tax code, we surveyed 1200 Latter‐day Saints about their practice of tithing. Tithing is similar to a flat tax with no deductions, where individuals voluntarily contribute 10% of self‐defined income to the church. The results of our survey indicate that most respondents operate on a cash realization basis, which excludes savings and does not allow any deductions. Respondents' income concepts generally do not coincide with current tax laws or economists' views of comprehensive income.     

Review Essay: What Is Left of the Left?

Sociological Forum -     

The philosophical foundations of Las Vegas

Las Vegas is a city that has long challenged social norms of the rest of the United States and built a highly successful economic base on gambling and other hedonistic pursuits. Now that many other states and communities are pursuing or actively considering following the route of legal casinos for economic development purposes, the ethical considerations that have confronted Las Vegas about the question of gambling and its broader social impacts take on greater import.This paper examines the ethics of gambling relative to Las Vegas at two levels: first, as a pragmatic trade-off of accepting an activity with some bad consequences because of the economic benefits that can be derived; and second, more fundamentally, by examining the validity of the major ethical arguments against gambling.     

A Comparison of Partially Adaptive and Reweighted Least Squares Estimation

The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokur-totic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators.     

Membranes, mitochondria and amoebae: shape models

Most real-world shapes and images are characterized by high variability- they are not rigid, like crystals, for example—but they are strongly structured. Therefore, a fundamental task in the understanding and analysis of such image ensembles is the construction of models that incorporate both variability and structure in a mathematically precise way. The global shape models introduced in Grenander's general pattern theory are intended to do this. In this paper, we describe the representation of two-dimensional mitochondria and membranes in electron microscope photographs, and three-dimensional amoebae in optical sectioning microscopy. There are three kinds of variability to all of these patterns, which these representations accommodate. The first is the variability in shape and viewing orientation. For this, the typical structure is represented via linear, circular and spherical templates, with the variability accomodated via the application of transformations applied to the templates. The transformations form groups: scale, rotation and translation. They are locally applied throughout the continuum and of high dimension. The second is the textural variability; the inside and outside of these basic shapes are subject to random variation, as well as sensor noise. For this, statistical sensor models and Markov random field texture models are used to connect the constituent structures of the shapes to the measured data. The third variability type is associated with the fact that each scene is made up of a variable number of shapes; this number is not assumed to be known a priori. Each scene has a variable number of parameters encoding the transformations of the templates appropriate for that scene. For this, a single posterior distribution is defined over the countable union of spaces representing models of varying numbers of shapes. Bayesian inference is performed via computation of the conditional expectation of the parametrically defined shapes under the posterior. These conditional mean estimates are generated using jump-diffusion processes. Results for membranes, mitochondria and amoebae are shown.