Predictable Pathways? Negotiating Risk in the Context of Marginalisation and Social Exclusion

This article is based on ethnographic research with young people living in an area of multiple deprivation in the North-east of England. The young people in this study experience many risk factors associated with social exclusion and future offending. Through in-depth examination of crime within the context of their lives, it will be argued that recent theorisations of youth crime and criminal careers do not fully capture the nature of their offending, the contextual circumstances surrounding it and the differential impact of similar risk factors on their lives. The article concludes by suggesting that not only do such theories detract from the situations of poverty and social exclusion in which young people live but that youth policies informed by them potentially add to their experiences of exclusion and marginalisation.

A Context-Dependent Algorithm for Merging Uncertain Information in Possibility Theory

The need to merge multiple sources of uncertaininformation is an important issue in many application areas,especially when there is potential for contradictions betweensources. Possibility theory offers a flexible framework to represent,and reason with, uncertain information, and there isa range of merging operators, such as the conjunctive anddisjunctive operators, for combining information. However, withthe proposals to date, the context of the information to be mergedis largely ignored during the process of selecting which mergingoperators to use. To address this shortcoming, in this paper,we propose an adaptive merging algorithm which selects largelypartially maximal consistent subsets (LPMCSs) of sources, thatcan be merged through relaxation of the conjunctive operator, byassessing the coherence of the information in each subset. In thisway, a fusion process can integrate both conjunctive and disjunctiveoperators in a more flexible manner and thereby be morecontext dependent. A comparison with related merging methodsshows how our algorithm can produce a more consensual result.