Research Notes

In the summer of 1995, a required MSW course was taught simultaneously to two sections of students at the University of Georgia, 11 on the main campus and 9 at a branch campus. Each section was alternately taught using live instruction or distance learning (two-way interactive television). At the conclusion of the course, students evaluated each method of teaching using Biner’s (1993) instrument for measuring attitudes toward televised courses. Live instruction was rated significantly higher than distance learning. Although distance learning technology has potential for augmenting social work educational resources, it has not yet demonstrated comparable outcomes in terms of student learning.     

Generating Probabilistic Spatially-Explicit Individual and Population Exposure Estimates for Ecological Risk Assessments

Exposure to chemical contaminants in various media must be estimated when performing ecological risk assessments. Exposure estimates are often based on the 95th-percentile upper confidence limit on the mean concentration of all samples, calculated without regard to critical ecological and spatial information about the relative relationship of receptors, their habitats, and contaminants. This practice produces exposure estimates that are potentially unrepresentative of the ecology of the receptor. This article proposes a habitat area and quality-conditioned exposure estimator, E[HQ], that requires consideration of these relationships. It describes a spatially explicit ecological exposure model to facilitate calculation of E[HQ]. The model provides (1) a flexible platform for investigating the effect of changes in habitat area, habitat quality, foraging area, and population size on exposure estimates, and (2) a tool for calculating E[HQ] for use in actual risk assessments. The inner loop of a Visual Basic program randomly walks a receptor over a multicelled landscape--each cell of which contains values for cell area, habitat area, habitat quality, and concentration--accumulating an exposure estimate until the total area foraged is less than or equal to a given foraging area. An outer loop then steps through foraging areas of increasing size. This program is iterated by Monte Carlo software, with the number of iterations representing the population size. Results indicate that (1) any single estimator may over- or underestimate exposure, depending on foraging strategy and spatial relationships of habitat and contamination, and (2) changes in exposure estimates in response to changes in foraging and habitat area are not linear.     

When was secularization? Dating the decline of the British churches and locating its cause1

Dating the decline of Christianity in Britain has a vital bearing on its explanation. Recent work by social historians has challenged the sociological view that secularization is due to long‐term diffuse social processes by asserting that the churches remained stable and popular until the late 1950s and that the causes of decline lie in the social and cultural changes associated with the 1960s. We challenge this interpretation of the evidence. We also note that much of the decline of the churches is explained not by adult defection but by a failure to keep children in the faith. Given the importance of parental homogamy for the successful transmission of religious identity, the causes of decline in one generation may well lie in the experiences of the previous generation. We focus on the disruptive effects of the 1939–45 war on family formation and use survey data to argue for a staged model of decline that is compatible with the conventional gradual view of secularization.     

‘Mobile mindsets’: EGM venue usage,gambling participation,and problem gambling among three itinerant groups on the Sunshine Coast of Australia

Mobile populations form an increasingly important part of many communities, yet tend to be neglected by problem gambling prevalence research. We explore relationships between problem gambling and the ways in which mobile subgroups use gambling venues. Adopting a combination of quantitative and qualitative techniques, we conduct an exploratory examination of three subgroups – construction workers, ‘grey nomads’, and ‘southerner’ tourists on the Sunshine Coast of Queensland, Australia. The groups displayed substantial differences in venue visitation, gambling behaviour and problem gambling risk. The group with the least discretionary mobility, the construction workers, were most heavily dependent on gambling venues for economic and social relationships. This translated into higher levels of problem gambling risk, which was further mediated by the inter-personal connectedness of individuals. These results suggest that mobility per se does not directly result in higher risk of problem gambling but combines with social isolation to place individuals at risk.     

The Marginalization of Nonresident Fathers: Their Postdivorce Roles

ABSTRACT

A sample of 260 Australian men were surveyed about their experience as nonresident fathers and their contact with their children. Most reported having little input into decisions concerning children's postseparation living arrangements, the amount of child support they paid, and the spending of their child support payments. Many claimed to have very limited say in any parenting decisions, and little or no involvement in children's schools. Fathers' limited parental role was found to be negatively correlated with their ongoing contact and involvement with children, and positively with their reported level of interparental hostility. Many respondents viewed their marginalization as parents as an impediment to their capacity to develop meaningful relationships with their children.     

A fourier integral density estimate: a Monte Carlo study

Davis (1977) proposed the use of a kernel density estimate which is the sample characteristic function integrated over (-A(n) , A(n)), where A(n) is chosen to minimize the mean integrated square error of the estimate. The scalar, A(n), is determined by the sample size and the population characteristic function. This paper investigates, in a Monte Carlo study, the mean integrated square error obtained under a procedure suggested by Davis (1977) for estimating A(n) when the population characteristic function is unknown.     

Improving communication via quantitative management

Villa Soft Drinks Ltd, established in 1884, manufactures and bottles spring waters and carbonates for both the growing adult soft drinks market and the more traditional soft drinks market. The company employs just over 100 people split between the manufacturing site in Sunderland and the head office and distribution centre in Washington. One of the fundamental problems affecting the day-to-day running of Villa, and most companies, is communication. There is a lack of awareness of the impact that changes in one department have on other departments (e.g. if production efficiency is increased by 10%, what impact will this have on warehousing?). Villa had recently identified key performance indicators (KPIs) to monitor all aspects of manufacturing performance on a regular basis. This enabled the current production situation to be evaluated and helped familiarize staff with charts and measurements. The use of Pareto analysis and problem solving techniques helped to boost efficiency and utilization. Key performance indicators were then developed in most other departments and are monitored and displayed regularly. The KPIs can be used further to improve transparency across the company by incorporating them in an interactive, interpretative tool to aid communication and understanding at all levels of the company. Individual departmental flow diagrams will be linked together to represent how the company operates. The diagrams will include both material flow and information flow. These data will then be organized in a software package and the end result will be a fully integrated simulation of the company in which any variable can be altered to demonstrate the effect this has on other departments and therefore the company as a whole. This will be an extremely valuable tool for the company as it will have many different applications, such as calculating manning requirements, identifying potential cycle time reductions and optimizing warehouse space.