How to Choose between Policy Proposals: A Simple Tool Based on Systems Thinking and Complexity Theory
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Complexity and systems approaches can be applied for the creation and evaluation of policy proposals. However, those approaches are difficult to learn and use. Therefore, those conceptual tools are not available to the general public. If citizens were able to analyze policies for themselves with relative ease, they would gain a powerful tool for choosing and improving policy. In this paper, I present a relatively simple method that can be used to measure the structure (complexity and co-causal relationships) of competing policies. I demonstrate this method by conducting a detailed comparison of two economic policies that have been put forth by competing political parties. The results show clear differences between the policies that are not visible through other forms of analysis. Thus, this method serves as a "David's sling"-a simple tool that can empower individuals and organization to have a greater influence on the policy process.INTRODUCTIONOur world faces a growing list of concerns including war, poverty, drugs, crime, environmental crisis, and economic collapse. The way that we understand and organize ourselves to engage these problems is through the creation and application of policy. Those policies are based on expert analysis. However, a growing body of research suggest that policy experts are unable to develop effective policy for dealing with these issues (Rhodes, 2008). Indeed, it could be said that our global problems are a result of our shared lack of policy competence.Because we lack policy competence, we cannot develop a single, shared, policy that is unarguably effective. As a result, each political party creates their own policy and claims that their version of policy will solve our problems (if we elect them into office). This has the result of placing the voting public in the very difficult situation of trying to choose between policies without a good understanding of how such a decision might best be made. In this paper, I will present and demonstrate a tool that will empower voters to make more effective policy choices.An economic policy serves as a map, reflecting each party's understanding of the economy and how it may be improved. In the present election cycle, as I write this article, each party has posted their economic policy on their official website. The voters must choose between those policies by voting for the party's candidates. However, for choosing policies, we have no tool more effective than intuition. And, as any gambler can tell you, intuition is not very reliable.More information is often said to be helpful in making that kind of decision. Yet, acquiring information is a "cognitively taxing task" (Redlawsk, 2004: 595). So-called 'factual' evidence is problematic because of underlying assumptions (MacGillivray & Gallagher, 2012). And, even when we do have the information, the amount of information obtained by voters may not have a large effect on voters' decisions (Carmines and Stimson 1980). Certainly, that information-based approach has not proved useful thus far.Indeed, what we have here is a "wicked" problem (Rittel 8i Webber, 1973). For such problems the normal, linear, approaches of science will not provide useful solutions. Our lack of ability to develop and choose policy means that the adoption of policy is based (at least in part) on the cultural and religious norms of a society (Simmons & Elkins, 2004). That is to say, in many instances, tradition and habit may be more influential than knowledge and logic. This is bad news if our tradition has become one of making poor economic policy.Without a reliable tool for choosing between competing policies, debate becomes divisive instead of constructive. The sides become polarized. Society becomes fragmented and democracy comes one step closer to failure.Systems thinking (ST) and complexity theory (CT) have been suggested as ways to gain a better understanding of policy problems (Dennard, Richardson & Morcol, 2008a; Morcol, 2010). …