1. This article proposes the concept of social multi-criteria evaluation (SMCE) as a possible useful framework for the application of social choice to difficult policy problems.
2. The foundations of SMCE are set up by referring to concepts from complex system theory and philosophy, such as reflexive complexity, post-normal science and incommensurability.
3. Technical incommensurability and social incommensurability are discussed in relation to multi-criteria decision making, with an example case study on water resource management in Palermo, Sicily.
The article “Social Multi-Criteria Evaluation: Methodological Foundations and Operational Consequences” is a well-written and comprehensive overview of the concept of Social Multi-Criteria Evaluation (SMCE). The author provides a clear explanation of the concept and its implications for decision making in public policy contexts. The article is based on sound theoretical foundations from complex system theory and philosophy, such as reflexive complexity, post-normal science and incommensurability. Furthermore, the author provides an example case study on water resource management in Palermo, Sicily which helps to illustrate how SMCE can be applied in practice.
The article is generally reliable and trustworthy; however there are some potential biases that should be noted. Firstly, the author does not provide any counterarguments or alternative perspectives on SMCE which could have been beneficial for providing a more balanced view of the topic. Secondly, there is no discussion of potential risks associated with SMCE which could have been explored further. Finally, it should also be noted that the example case study provided is limited to one particular context (water resource management in Palermo) which may not be representative of other contexts where SMCE could be applied.
In conclusion, this article provides a thorough overview of Social Multi-Criteria Evaluation (SMCE) with sound theoretical foundations and an illustrative case study; however there are some potential biases that should be noted such as lack of counterarguments or alternative perspectives on SMCE as well as lack of discussion about potential risks associated with its application.