Public Sociology and the Public Turn in the Social Sciences

Public sociology broadly conceptualized is a form of intellectuality involving dialogue between sociologists and the publics with whom they are concerned. Beyond this broad framing, what type of dialogue, with what purpose, which public(s), and the functions of intellectuals and the knowledge they produce are widely contested. In this essay, I explore the politics of academic disciplines, knowledge, and discourse as it has emerged within the debate over public sociology, while also highlighting what public sociology and the rise of other ‘public’ disciplines tells us about these themes in relationship to the possibility of public culture.     

Posture Development in Infants at Heightened versus Low Risk for Autism Spectrum Disorders

Evidence suggests that children and adults diagnosed with autism spectrum disorders (ASD) exhibit difficulties with postural control. Retrospective video studies of infants later diagnosed with ASD indicate that infants who eventually receive an ASD diagnosis exhibit delays in postural development. This study investigates early posture development prospectively and longitudinally in 22 infants at heightened biological risk for ASD (HR) and 18 infants with no such risk (Low Risk; LR). Four HR infants received an autism diagnosis (AD infants) at 36 months. Infants were videotaped at home at 6, 9, 12, and 14 months during everyday activities and play. All infant postures were coded and classified as to whether or not they were infant‐initiated. Relative to LR infants, HR infants were slower to develop skill in sitting and standing postures. AD infants exhibited substantial delays in the emergence of more advanced postures and initiated fewer posture changes. Because posture advances create opportunities for infants to interact with objects and people in new and progressively more sophisticated ways, postural delays may have cascading effects on opportunities for infant exploration and learning. These effects may be greater for infants with ASD, for whom posture delays are more significant.     

Knowing and Governing: The Mapping of the Nonprofit and Voluntary Sector as Statecraft

Recent debate in Voluntas and elsewhere has paid a great deal of attention to the subject of mapping the nonprofit sector. However, very little attention has been paid to the ways in which the practice of mapping is a political mode of knowing and the ways in which knowing is governing. In this essay, we turn to critical theory and political anthropology in order to demonstrate how mapping as it is currently practiced is a mode of knowledge inquiry that facilitates statecraft. In light of these interdisciplinary perspectives, we wrestle with the implications of knowing—and thereby governing—voluntary collective organization in this manner. We conclude that this approach potentially disciplines the qualitative dimensions of democratic associational life and misrepresents the possibilities of social change.     

The maximum dispersion problem

In the maximum dispersion problem, a given set of objects has to be partitioned into a number of groups. Each object has a non-negative weight and each group has a target weight, which may be different for each group. In addition to meeting the target weight of each group, all objects assigned to the same group should be as dispersed as possible with respect to some distance measure between pairs of objects. Potential applications for this problem come from such diverse fields as the problem of creating study groups or the design of waste collection systems. We develop and compare two different (mixed-) integer linear programming formulations for the problem. We also study a specific relaxation that enables us to derive tight bounds that improve the effectiveness of the formulations. Thereby, we obtain an upper bound by finding in an auxiliary graph subsets of given size with minimal diameter. A lower bound is derived based on the relation of the optimal solution of the relaxation to the chromatic number of a series of auxiliary graphs. Finally, we propose an exact solution scheme for the maximum dispersion problem and present extensive computational experiments to assess its efficiency.     

Guaranteed Renewability with Group Insurance

This paper investigates a multiple-period level premium insurance policy equilibrium in a model in which loss probabilities increase for a fixed time period for a set of persons buying insurance in a group. We show that a level-premium sequence which induces risk averse persons to become and remain members of the group exists. We also show that the availability of the Medicare program can prevent the emergence of optimal level-premium private group insurance, but that a system of bonuses for remaining in the group can permit optimality to be retained.     

A multi-stage stochastic supply network design problem with financial decisions and risk management

In this paper, a multi-period supply chain network design problem is addressed. Several aspects of practical relevance are considered such as those related with the financial decisions that must be accounted for by a company managing a supply chain. The decisions to be made comprise the location of the facilities, the flow of commodities and the investments to make in alternative activities to those directly related with the supply chain design. Uncertainty is assumed for demand and interest rates, which is described by a set of scenarios. Therefore, for the entire planning horizon, a tree of scenarios is built. A target is set for the return on investment and the risk of falling below it is measured and accounted for. The service level is also measured and included in the objective function. The problem is formulated as a multi-stage stochastic mixed-integer linear programming problem. The goal is to maximize the total financial benefit. An alternative formulation which is based upon the paths in the scenario tree is also proposed. A methodology for measuring the value of the stochastic solution in this problem is discussed. Computational tests using randomly generated data are presented showing that the stochastic approach is worth considering in these types of problems.