Extreme Value Statistics and Traveling Fronts: Various Applications

An intriguing connection between extreme value statistics and traveling fronts has been found recently in a number of diverse problems. In this brief review we outline a few such problems and consider their various applications.Comment: A brief review (6 pages, 2 figures) to appear in Physica A as part of the proceedings of Statphys-Kolkata IV (2002

Connection men, pushers and migrant trajectories: examining the dynamics of the migration industry in Ghana and along routes into Europe and the Gulf States

This paper examines the inner workings and operational logic of the array of individuals, agencies, state and non-state actors, institutions and social networks that collectively make up the migration industry in Ghana. It sheds light on how actors in the migration industry facilitate and condition migrant mobility, focusing on workers moving from Ghana along two migration corridors towards Europe and the Gulf States for work in the domestic and construction sectors. The study draws on a broad and nuanced conceptualisation of the “migration industry” which goes beyond a narrow focus on actors operating mainly for financial gain. Instead, it focuses on migration not just as a movement from point of departure to arrival, but as a changing journey over both space and time. This allows not only empirical insights into the processes through which people move, but it also provides an analytical lens to better unpack the complexities of migration processes. We extend the analysis of migration industries by incorporating risk theory into the analysis of the migration decision. The decision takes place in a context where migrants’ high level of knowledge about the dangers of migration has not translated into a reduction in migration flows on these two corridors. We analyse migrants’ rationale for choosing to embark on highly risky journeys, even in the face of increasing knowledge about these risks, and to develop appropriate policy responses

Development and Use of an Agent-based Model to Assess the Effect of Forecast Credibility on Urban Traffic During Snow Events

With the difficulties in snow accumulation prediction, the potential for false alarms and forecast misses arise. These forecast errors can lead to a lack of public trust and poor decisions in responding to future weather hazards. There has been little research on how individuals respond in the future to false alarms and forecast inconsistencies. We developed an agent-based traffic model to demonstrate how snow forecasts and public response interplay. This model factors receptiveness to expertise, forecast severity, and forecast credibility into the agents’ work-related travel decisions. Agents are grouped into three categories: firm workers, service workers, and household workers, where firm workers can work from home, service workers must go into work, and household workers always work from home. It was found that forecast severity has the most effect on the number of agents traveling, while credibility factors into agents’ decisions if they have the option to work from home. Owing to uncertainties in actual accident rates during snowfall, no firm conclusions were made in terms of how such events might interact with forecast severity and credibility, although there does appear to be potential for significant regional differences in these effects. This model is a first attempt at simulating the role that these factors play in work-related travel decisions and outcomes, but it is deliberately simple. Recommendations are made regarding useful enhancements to the model framework