| dc.description.abstract | Models and indexes are increasingly being used to help make better substantiated decisions in pol-icy-making processes. Models and indexes themselves have improved enormously in the last dec-ades due to better data-gathering techniques and IT technology. However, models are often seen in processes of policy making as ‘neutral black boxes’ that are not questioned, and policy makers often follow its results. This research focuses on the effect of choices and assumptions made while creating a model on the model-based suggestions for policymakers. This is done with a case study on the Urban Climate Risk Index (UCRI), an index that is designed to assess climate risks in cities on a global scale. This is analysed using the Social Construction of Technology (SCOT) approach. It be-came clear that the choices and assumptions made when designing the index have a major impact on the results of the index. Furthermore, the biases and interests of modellers, stakeholders and commissioners also influence how an index is created, which in turn influences the results of the index. Therefore, a deeper recognition and exploration of the processes involved in the creation of models and indexes, the presentation of results, and their use for policy design is needed. This will help in building an understanding of the role of indexes and models in the governmental domain. It is also important that the underlying biases in models and indexes are discussed between stake-holders, scientists and policymakers. This will make policy-making processes that use models and indexes more democratic. | |
