As part of the project “Linking Borderlands”, Prof. Dr. Peter Starke who teaches at the University of Southern Denmark held a presentation on diffusion mechanisms at TU Kaiserslautern. Participants were able to join in presence as well as on Zoom on Friday, October 15th.
Diffusion research focuses on how and why policies spread between states, regions, and cities. In doing so, researchers differentiate mainly between the mechanisms learning, emulation and competition. For example, a state can be interested in solving domestic problems by looking for solutions abroad, thus learning from others. However, states can also be inclined to engage in competition with others, for example by adjusting their tax levels. While theoretically, this distinction is shared by most researchers, the operationalization proves difficult: Looking at past studies, different mechanisms are often measured with the same indicators, while different indicators are used to measure the same mechanism. For example, geographical proximity and structural similarity have been used as indicators for all three mechanisms.
Hence, Peter Starke proposes a different strategy by employing the mechanistic philosophy of science by Machamer, Darden and Craver. In this perspective, causality is no longer operationalized by a set of independent and dependent variables but in a more organic way. The focus here lies on ‘causally productive’ entities and activities which lead to a certain outcome. Empirically, this implies a shift towards paying closer attention to the actions of actors which engage in policy diffusion processes. One possible strategy lies in using text analytical methods to extract those activities – are political actors drawing lessons, observing, and learning or are they improving a country’s international position, developing an advantage, and competing?
While research is only just now starting to think about such alternative ways to classify and measure diffusion mechanisms, it surely is a promising start to exit the methodological impasse it has entered long ago.