Ed Ferrari

AIMSS: An Architecture for Data Driven Simulations in the Social Sciences

This paper presents a prototype implementation of an intelligent assistance architecture for data-driven simulation specialising in qualitative data in the social sciences. The assistant architecture semi-automates an iterative sequence in which an initial simulation is interpreted and compared with real-world observations. The simulation is then adapted so that it more closely fits the observations, while at the same time the data collection may be adjusted to reduce uncertainty. For our prototype, we have developed a simplified agent-based simulation as part of a social science case study involving decisions about housing. Real-world data on the behaviour of actual households is also available. The automation of the data-driven modelling process requires content interpretation of both the simulation and the corresponding real-world data. The paper discusses the use of Association Rule Mining to produce general logical statements about the simulation and data content and the applicability of logical consistency checking to detect observations that refute the simulation predictions.

The housing and neighbourhood impacts of knowledge-based economic development following industrial closure

Economic development initiatives following large-scale industrial closures often seek to regenerate the local economy through investment in technology and knowledge-intensive activities. The resulting changes in the make-up of the local workforce are in turn likely to generate new forms of demand for housing; demand that will not necessarily be met by the residential offer of the neighbourhoods worst affected by the initial closure. This paper explores these processes through a study of the proposals for a science park as a component of the programme to redevelop the Longbridge site in Birmingham in the UK, following the closure of the Rover automotive plant in 2005. The paper examines the capacity of local workers to take up the anticipated high-technology jobs; the likely configuration of an incoming workforce; and the fit between the housing requirements of these new workers and the residential offer of neighbourhoods in the Longbridge area. It concludes that there is likely to be a poor match between the housing and residential characteristics of neighbourhoods most closely associated with the plant closure and the requirements of an incoming high-tech workforce. This in turn raises a policy dilemma. On the one hand there is a necessity to secure economic diversification for the local economy as a whole, whilst on the other is the requirement to address the specific needs of the discrete neighbourhoods most affected by the closure and whose quality of place offer is often furthest from the requirements of the incoming workforce. A number of policy implications are discussed, drawing on the experience of recent housing and regeneration policy.

Competing Ideas of Social Justice and Space: Locating Critiques of Housing Renewal in Theory and in Practice

Abstract This article considers the experience of the English governments policy of Housing Market Renewal from the perspective of spatial justice. The paper first proposes an analytical framework that situates competing notions of territorial social justice within a space of complex sociospatial relations. The dialectic of two formulations of social justice is first set up, comparing ‘procedural’ or deontological forms of justice and the distributional justice of outcomes. Sojas formulation of spatial justice is advanced as an appropriate balance between spatial and socio-historic contexts for the justice question. Drawing on the literature on sociospatial relations, concrete critiques and justifications of HMR are then positioned in terms of the intersection of structuring principles and policy fields. The role of demolition in urban restructuring programmes is used to explore the differential spatialities involved in different justicial perspectives. It is concluded that ‘gentrification’ critiques of HMR are only partial in their evaluation of justice and lack normative power. Some practical implications for the design of urban restructuring policies are offered.

Knowing the Area: The Management of Market and Business Risks by Private Landlords in Scotland

Compared with the management of social rented housing in Britain, comparatively little is known about how private landlords manage their property, despite their increasing importance. This paper reports results from a recent survey in Scotland which shows that landlords restrict the acquisition of property close to where they themselves live to manage the market and business risks they face. This is because their personal knowledge of markets is important in reducing risks, given the complexities of the sub-markets where they operate and the information asymmetries involved. The paper combines quantitative data on a large sample of properties in Scotland and their landlords, including the location of their properties and homes (or businesses), with a series of focus groups with a smaller sample to understand the reasons why most landlords live very close to their portfolios. The policy implications of the results of the surveys are also discussed.

Conceptualising Social Housing within the Wider Housing Market: A Vacancy Chain Model

There have been increasing calls for studies of housing systems that are more integrative and pluralistic in nature. Understanding the relationship of social housing systems to the wider housing market remains a key challenge. The mobility of households and the structural configuration of supply are both of importance, demanding methods able to reconcile both. This paper propounds vacancy chain models as offering significant potential in this regard, allowing policy analysis and options appraisal to be built on more dynamic conceptualisations of housing systems. The theoretical basis for vacancy chain models is developed before an account is given of a model developed of the Bradford (UK) social rented sector. The results suggest that social renting is very closely linked to the wider housing market and consequently the impacts of policy and investment may be felt beyond the sector. Observations on the future development of vacancy chain models are offered.

The Social Value of Housing in Straitened Times: The View from England

This paper provides a commentary on the contemporary housing crisis in England and links it to broader questions of role of housing in capitalist economies and societies. It starts with the assumptions that housing and community development issues are linked to the wider housing market and that the housing crisis is not new but has long-run antecedents. The paper begins by reviewing the contemporary terrain of housing markets and policies in the UK. It then discusses several aspects of ‘crisis’: market volatility, rates of new supply, affordability, state welfare subsidies and socio-spatial inequalities. Policy responses to these are examined through a discussion of efforts to expand the role of the private rented sector, sell-off ‘expensive’ public housing and curtail market renewal investments. The paper concludes that current conceptualisations of the value of housing are often partial and insufficiently integrative and that policies must explicitly recognise housing as a social and economic asset.

New housing association development and its potential to reduce concentrations of deprivation: An English case study

Social housing across Western Europe has become significantly more residualised as governments concentrate on helping vulnerable households. Many countries are trying to reduce the concentrations of deprivation by building for a wider range of households and tenures. In England this policy has two main strands: (1) including other tenures when regenerating areas originally built as mono-tenure social housing estates and (2) introducing social rented and low-cost homeownership into new private market developments through planning obligations. By examining where new social housing and low-cost home ownership homes have been built and who moves into them, this paper examines whether these policies achieve social mix and reduce spatial concentrations of deprivation. The evidence suggests that new housing association development has enabled some vulnerable households to live in areas which are not deprived, while some better-off households have moved into more deprived areas. But these trends have not been sufficient to stem increases in deprivation in the most deprived areas.

Data Driven Simulation to Support Model Building in the Social Sciences

Artificial intelligence (AI) can contribute to the management of a data driven simulation system, in particular with regard to adaptive selection of data and refinement of the model on which the simulation is based. We consider two different classes of intelligent agent that can control a data driven simulation: (a) an autonomous agent using internal simulation to test and refine a model of its environment and (b) an assistant agent managing a data-driven simulation to help humans understand a complex system (assisted model-building). We present a prototype implementation of an assistant agent to apply DDDAS to social simulations. The automation of the data-driven model development requires content interpretation of both the simulation and the corresponding real-world data. The paper discusses the use of Association Rule Mining to produce general logical statements about simulation and data content as well as the use of logical consistency checking to detect observations that refute the simulation predictions. Finally we consider ways in which this kind of assistant agent can cooperate with autonomous data collection and analysis agents to build a more complete and reliable picture of the observed system.

Towards an Automated Approach to Dynamic Interpretation of Simulations

Representation and interpretation of simulation semantic content is a challenging problem at the heart of issues such as simulation composability and symbiotic simulation. This paper introduces an automated approach to dynamic online interpretation of simulations using AI techniques. The approach is described in the context of agent-based social simulations

Small-Area Spatial Statistics

The analytic possibilities of the digital age have been opened up profoundly by the exponential increase in geo-referenced data sets at the small-area level. Widespread adoption of geographical information systems and allied technologies has created a hunger for spatially referenced information on nearly all aspects of social and economic life.