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Top1. Introduction
The challenges of nowadays dynamic societies to ensure social welfare, economic growth and jobs impose capacities of dealing with complexity in policy choices by governments. The strong impact of policy decisions on the wellbeing of societies and of economies require that governments work more closely with the respective stakeholders in particular policy contexts when making such decisions. Consequently, adequate support is needed to overcome current weaknesses in policy decision making.
Especially the recent economic and financial crisis, which resulted also from our inability to predict dramatic changes in the economy and society and/or ignoring those few individuals who were warning the governments before these threats and negative trends, sheds light on an urgent need for more effective and efficient processes of governance and policy making.
Challenges and deficiencies of current policy development emerge from a long history of scientific development that resulted in the need to engage stakeholders in the design and evaluation of models of social processes, from which it was a small and natural step to use the models for purposes of social policy analysis and which itself required the engagement of the stakeholders in policy analysis. A driving force of this scientific development was the combination of two specific failures of prevailing social theory and related social modelling.
The first of these failures has been the patent inability of social scientists to forecast the timing, magnitude or duration of such extreme events as the recent credit crisis and recession. Despite a widespread search of the academic literature and the mass media and public enquiries via relevant newsgroups and discussion lists, the authors have not been able to identify a single, correct, model-based forecast of a turning point in either macroeconomic trade cycles or financial market indices in the whole history of economic forecasting. This problem has implications of enormous, global significance since macroeconomic and econometric models are central to the understanding of economists and the advice they give in the process of policy formation. Different models imply and inform different policies. The effects of stabilization policies and recovery plans, the magnitude of problems attendant upon protectionist policies, the need for financial support for individuals and enterprises are all assessed by the use of economic and econometric models.
The second failure is the lack of connection between scientific and informal observation of human behaviour and social interaction on the one hand and, on the other, the specification of behaviour by constrained optimisation algorithms and the assumption that there is no social interaction in many social (and all mainstream economic) policy models. The explanation for the systematic (and possibly complete) forecasting failure emerged in parallel and in mutual ignorance of one another in two branches of the scientific literature: statistical physics and agent-based social simulation modelling.
In consequence, a new approach is necessary that builds on evidence-based user-driven development of policy texts, which informs a formal policy model to elicit potential interdependencies, and which enables a simulation model as correct and precise as possible. The development of the user-generated scenario models and the formal simulation models needs to be iterative and needs to enables different relevant stakeholders to interact and contribute to the evidence-based policy texts.
With this view of needing proper support in policy development, the project OCOPOMO was developed. OCOPOMO (Open Collaboration in Policy Modelling, www.ocopomo.eu) is a project co-funded in the seventh framework programme of the European Commission (2007). When developing the OCOPOMO project, a number of weaknesses were identified in current policy development practices, for example: