Attaining social value from electronic government

We define and elaborate a Social Value framework supporting evaluation and attainment of the broader socio-political and socio-economic goals that characterise many electronic government initiatives. The key elements of the framework are the willingness of citizens to (positively) recommend an e-government service to others, based upon personal trust in the service provider, and personal experience of the service, based upon experience of service provision and outcomes. The validity of the framework is explored through an empirical quantitative study of citizens' experiences of a newly introduced e-government system to allocate public social housing. The results of this study include evidence of generic antecedents of trust and willingness to recommend, pointing the way to more general applicability of the framework for designers and managers of electronic government systems

Income Inequality as a Political Issue: Does it Matter?

Income inequality has been increasing since the early 1970s, but there has been little analysis of whether American voters consider this issue when casting a ballot. This study combines survey data from the 2012 American National Election Study with Gini coefficients at the Congressional district level to evaluate whether attitudes about income inequality and actual income inequality have a significant impact on vote choice for Congressional candidates in the 2012 election. As control variables are added, predictor questions about income inequality remain significant, while Gini coefficients become statistically insignificant. This analysis provides evidence that attitudes about income inequality as a political issue have a more important influence on vote choice than do actual conditions at the district level

Causal and Non-Causal Explanations of Artificial Intelligence

Deep neural networks (DNNs), a particularly effective type of artificial intelligence, currently lack a scientific explanation. The philosophy of science is uniquely equipped to handle this problem. Computer science has attempted, unsuccessfully, to explain DNNs. I review these contributions, then identify shortcomings in their approaches. The complexity of DNNs prohibits the articulation of relevant causal relationships between their parts, and as a result causal explanations fail. I show that many non-causal accounts, though more promising, also fail to explain AI. This highlights a problem with existing accounts of scientific explanation rather than with AI or DNNs

Timber Related Source Materials about Mississippi\u27s Piney Woods: An Archival Survey of the McCain Library and Archives at the University of Southern Mississippi

Few natural resources impacted the lives of Mississippians to the degree which timber has. In particular, the southeastern and south central regions of the state received the label piney woods because the dominant features of the region consisted of longleaf, shortleaf, loblolly, and slash pines. Early Mississippians might have labeled other regions of the state according to the soil content, but the towering conifers which proliferated from the Gulf Coast northward to Jackson, and westward to near Natchez, seemed the main economic resource by which to label the area. The purpose of this article is to detail briefly why timber has been a major factor in the development of the region, and more important, how a survey of related archival materials, specifically materials at the McCain Archives at the University of Southern Mississippi, can be of benefit to researchers in several disciplines, including forestry, history, environmental studies, biology, and anthropology. A secondary, but nonetheless important objective of the work is to provide a reference resource for librarians which can be used as an introduction to the primary archival sources on Mississippi\u27s piney woods housed at the McCain Library and Archives