Suicide and rurality in Alabama communities

Empirical research findings suggest that suicide increases with rurality, but research on rural suicide leaves many questions unanswered. This study specifies problems of community organization as a reason for expecting a positive effect of rurality on the suicide rate. A multiple regression analysis of county data shows that rurality has a substantial positive effect and is, in fact, the best predictor of the suicide rate among several variables selected from the previous literature. Additional research is needed to test the interpretation that rurality contributes to an incomplete, fragmented form of community organization which influences the suicide rate by disrupting primary relationships.     

Composable models for online Bayesian analysis of streaming data

Data is rapidly increasing in volume and velocity and the Internet of Things (IoT) is one important source of this data. The IoT is a collection of connected devices (things) which are constantly recording data from their surroundings using on-board sensors. These devices can record and stream data to the cloud at a very high rate, leading to high storage and analysis costs. In order to ameliorate these costs, the data is modelled as a stream and analysed online to learn about the underlying process, perform interpolation and smoothing and make forecasts and predictions. Conventional state space modelling tools assume the observations occur on a fixed regular time grid. However, many sensors change their sampling frequency, sometimes adaptively, or get interrupted and re-started out of sync with the previous sampling grid, or just generate event data at irregular times. It is therefore desirable to model the system as a partially and irregularly observed Markov process which evolves in continuous time. Both the process and the observation model are potentially non-linear. Particle filters therefore represent the simplest approach to online analysis. A functional Scala library of composable continuous time Markov process models has been developed in order to model the wide variety of data captured in the IoT.     

Distinctive policy diffusion patterns,processes and actors: drawing implications from the case of sport in international development

This article examines the diffusion of “Sport for Development and Peace” (SDP) across sub-Saharan Africa following global policy impetus provided by international organizations, including the United Nations, since the start of the twenty-first century. In so doing, the article centres on a geographical region that has been unconsidered in the policy diffusion literature and, particularly, responds to calls for research into the effects of policy characteristics on diffusion mechanisms and patterns. This rationale beget methods that differed from the predominant use of quantitative, dichotomous indicators of policy diffusion, instead integrating data from global, international and national policy documents, from a review of SDP literature, and from stakeholder interviews in Ghana and Tanzania. Patterns of increasing governmental engagement with, but limited implementation of, SDP policies contrasted with the significant expansion of SDP provision by diverse NGOs. In turn, these patterns represented the varying influence of different diffusion mechanisms on state and non-state actors. Compared with the diffusion of other types of policies, these findings indicated the effects of an instrumental, malleable but complex global policy model for SDP diffusion. There is, therefore, significant value in further research that examines how policy diffusion may depend on the configuration of particular policy characteristics, mechanisms and actors.     

SIMULATING FOOD SHOPPERS' ECONOMIC LOSSES AS A RESULT OF SUPERMARKET UNAVAILABILITY*

This study illustrates a methodology as a first step toward the development of a benefit/cost model for the evaluation of the Federal Trade Commission regulation of the unavailability of advertised specials in food stores. A Monte Carlo simulation was used to estimate economic losses to shoppers from unavailable advertised specials. Product unavailability in the model occurred as a result of alternative managerial decisions about purchase-order quantities for advertised specials and shelf-stocking policies combined with probabilistic purchase decisions by customers. The model generated probabilistic individual customer and management behavioral responses to unavailability during a one-year time period. As a result, the derived economic losses to customers from unavailability were based on alternative assumptions about managerial behavior in conjunction with empirically derived shopper responses to advertised specials. This study thus provides some idea of the amount of damages being caused by the excessive unavailability of advertised specials. Aggregate customer losses were found to vary primarily with respect to management's purchase-order quantity of advertised specials.     

Messiahs, Pariahs, and Donors: The Development of Social Representations of Organ Transplants

This longitudinal, qualitative study investigated the genesis and transformation of the social representations of organ transplants. A search of the West Australian newspaper, from 1954 to 1995 found 672 articles pertaining to organ transplants. Two distinct, but conflicting, representations emerged in the analyses. In the first representation, found from 1967/68, the surgeon was paramount and organ transplants were iconised as 'spare part surgery'. In the second representation, found from 1984/85, the role of the donor was emphasised and transplants iconised as a 'gift of life'. Both representations were discernible in 1994/95. We consider the question whether there are now two conflicting representations or one representation with two conflicting sets of beliefs at its core. The results are discussed in terms of anchoring, objectification, transformation, and structure, as well as Moscovici's (1993) notion of canonic themata.     

Where's the beef? A response to Gray and Webb's ‘The return of the political in social work’

Gray and Webb's article 'The return of the political in social work' is a welcome contribution to current debates. In its critique of the dominance of calculative reason, its rejection of postmodernism and identity politics, and its insistence on the need for social work to openly address issues of power and conflict, it is a useful addition to the growing critical literature concerned with challenging dominant forms of practice. That usefulness is limited, however, first by an excessively opaque style and, second, by problems associated with the writers' argument and approach. These include: an over-reliance on Heidegger's ontology; an over-estimation of the potential of art to act as alternative paradigm; and a particularly content-less version of politics, derived from the work of Alain Badiou, which is likely to prove to be of limited value in the project of developing alternative forms of social work.     

Using the EM algorithm for Bayesian variable selection in logistic regression models with related covariates

We develop a Bayesian variable selection method for logistic regression models that can simultaneously accommodate qualitative covariates and interaction terms under various heredity constraints. We use expectation-maximization variable selection (EMVS) with a deterministic annealing variant as the platform for our method, due to its proven flexibility and efficiency. We propose a variance adjustment of the priors for the coefficients of qualitative covariates, which controls false-positive rates, and a flexible parameterization for interaction terms, which accommodates user-specified heredity constraints. This method can handle all pairwise interaction terms as well as a subset of specific interactions. Using simulation, we show that this method selects associated covariates better than the grouped LASSO and the LASSO with heredity constraints in various exploratory research scenarios encountered in epidemiological studies. We apply our method to identify genetic and non-genetic risk factors associated with smoking experimentation in a cohort of Mexican-heritage adolescents.     

States of nature and states of mind: a generalized theory of decision-making

Canonical economic agents act so as to maximize a single, representative, utility function. However, there is accumulating evidence that heterogeneity in thought processes may be an important determinant of individual behavior. This paper investigates the implications of a vector-valued generalization of the Expected Utility paradigm, which permits agents either to deliberate as per Homo economics, or to act impulsively. This generalized decision theory is applied to explain the crowding-out effect, irrational educational investment decisions, persistent social inequalities, the pervasive influence of non-cognitive ability on socio-economic outcomes, and the dynamic relationships between non-cognitive ability, cognitive ability, and behavioral biases. These results suggest that the generalized decision theory warrants further investigation.