LawSync: navigating the ‘blue oceans’ within the ‘emerging’ legal services markets

Change, it is said, is the only constant. Whilst it cannot be avoided, the worlds of legal education and legal services have arguably enjoyed an extended period where the impact of change has been comparatively minimal. Today, these worlds face significant changes due to a combination of market and regulatory forces. True, such changes are likely to be accompanied by challenges but with these challenges come opportunities. There is no reason why Law Schools and Law students cannot help to shape these changes and benefit from them. LawSync™ is a project that seeks to enable such influence and attract such benefits at Sheffield Hallam University. See http://www.lawsync.com and http://twitter.com/lawsync for more details

Age in Relation to the Winter Food Habits and Helminth Parasites of the Bobcat (Lynx Rufus, Schreber) in Oklahoma

Wildlife Ecolog

Tabanidae Associated with White-tailed Deer in Different Habitats of Oklahoma and the Prevalence of Trypanosomes Resembling Trypanosoma Theiler! Laveran in Selected Species

Entomolog

An ML Editor based on Proofs-as-Programs

. C Y NTHIA is a novel editor for the functional programming language ML in which each function definition is represented as the proof of a simple specification. Users of C Y NTHIA edit programs by applying sequences of high-level editing commands to existing programs. These commands make changes to the proof representation from which a new program is then extracted. The use of proofs is a sound framework for analysing ML programs and giving useful feedback about errors. Amongst the properties analysed within C Y NTHIA at present is termination. C Y NTHIA has been successfully used in the teaching of ML in two courses at Napier University. 1 Introduction Current programming environments for novice functional programming (FP) are inadequate. This paper describes ways of using mechanised theorem proving to improve the situation, in the context of the language ML [9]. ML is a stronglytyped FP language with type inference [4]. ML incorporates extensive use of pattern match..

Do individuals’ risk and time preferences predict entrepreneurial choice?

This study seeks to estimate whether individuals’ risk and time preferences are predictive of self employment status and entry. Prior Work: The low risk aversion of those who are self employed is well established in theory and empirical evidence, there is less evidence however on whether risk seeking in existing employees predicts future self employment entry and virtually no empirical research on the links between time preference and self employment. Approach: This study uses a quantitative approach by estimating a series of statistical models that estimate the relationship between an individuals’ risk and time preferences and whether they are (or subsequently become) self employed using a national longitudinal dataset. Results: We find that the self employed are more likely to have low risk aversion. When restricting our analysis to those who are initially employees we find that , low risk aversion combined with a preference for short term gains are most predictive of a transition into self employment. Implications and Value: This study informs the general question as to whether entrepreneurship is linked to personality traits with new evidence on the link between risk and time preference and self employment entry, in doing so it points towards attitudes toward risk and time preference that need to be encouraged if entrepreneurship is to be developed within countries and firms

User Experience for Model-Driven Engineering : Challenges and Future Directions

Since its infancy, Model Driven Engineering (MDE) research has primarily focused on technical issues. Although it is becoming increasingly common for MDE research papers to evaluate their theoretical and practical solutions, extensive usability studies are still uncommon. We observe a scarcity of User eXperience (UX)-related research in the MDE community, and posit that many existing tools and languages have room for improvement with respect to UX [26], [44], [37], where UX is a key focus area in the software development industry. We consider this gap a fundamental problem that needs to be addressed by the community if MDE is to gain widespread use. In this vision paper, we explore how and where UX fits into MDE by considering motivating use cases that revolve around different dimensions of integration: model integration, tool integration, and integration between process and tool support. Based on the literature and our collective experience in research and industrial collaborations, we propose future directions for addressing these challenges

An empirical investigation into the propensity of reckless decision making within the high pressure environment of Deal or No Deal.

This paper discusses human attitudes towards risk and the development of expected utility models, laying the foundations for the creation of prospect theory in 1979. It proceeds to analyse the decisions of contestants on the popular TV game show Deal or No Deal to attempt to observe any evidence of differing levels of risk aversion under losses and gains as predicted by prospect theory. The results reveal some evidence of decreased risk aversion in the domains of losses and gains, with contestants displaying behaviour consistent with the break-even and house-money effects. We conclude there may be enough evidence of variable reference points to warrant further investigation, and propose suggestions for further researc