Using Integrative Propositional Analysis to Understand and Integrate Four Theories of Social Power Systems
Figure 1 : A simple abstract theoretical model .
In Figure 1 , A , B , and C refer to concepts that would represent something in the real world . For example , A might represent “ effective planning ”, while B might represent “ uncertainty ” and C might represent “ reliability of decisions .” For this example , more effective planning will result in more reliable decisions , while more uncertainty will lead to less reliable decisions . This representation is rather selective , simple , and incomplete — a limitation prevalent in many theories . Still , the example serves as an example for the application of IPA for now it is measurably incomplete .
In Figure 1 , the propositions of a theory have already been rendered into diagrammatic form and the causal linkages identified ( IPA steps one through three ). For step four in IPA , it is clear that there are three concepts ( A , B , C ) as depicted on the diagram . Therefore , the Complexity of this theoretical model can be represented as three ( for systems thinkers , please recall that this is the “ simple complexity ”). Step five is to identify the concatenated concepts . A concept is concatenated when there is more than one causal arrow pointing directly at it . Here , it is not relevant whether the causation is positive or negative . In Figure 1 , C is the only concept / variable with more than one arrow pointing toward it . Therefore , there is one concatenated concept / variable out of the three . The final step of IPA is to determine the overall Systemicity of the theory . This is done by ratio analysis , dividing the number of concatenated concepts / variables “ C ” ( one ) by the total number of concepts / variables ( three ) giving a Systemicity of 0.33 .
Complexity can be used as a measure to capture the “ breadth ” of the theory . Basically , how much conceptual ground is covered by the theory . Systemicity can serve as a measure of the “ depth ” of the theory , essentially , how well interconnected or how systemic the theory is . We hold that a theory that is more systemic can provide a more reliable representation of “ reality ” that is also held to be systemic in nature .
While theories are the source of data for IPA , the method is neutral or agnostic as to the source of data for developing the theories . That data may be qualitative or quantitative . And , according to the correspondence perspective , it is generally accepted that having more data will help to build better theories . One important benefit of IPA is that it provides an additional approach for developing better theories — adding a coherence approach to the more traditional correspondence approach . Theories with a higher lev-
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