Institute of Political Science

"Trust, don't verify" - Towards a theory of strong trust in International Relations

In the social sciences, trust is generally considered to be an important precondition for cooperation under uncertainity. It is all the more confounding, then, that trust has not attracted more attention from scholars of International Relations. There exists little theoretical work on trust in IR and there have been even less attempts to operationalize trust as a variable. This research project intends to attenuate these deficits in three ways: First, we will provide a concise and sophisticated theory of trust between states. Second, we will introduce a valid operationalization to measure interstate trust. Third, we will develop the first building blocks of a theory of trust-building in international politics.

Theoretically, we conceive of trust as 'strong trust'. That is, trust is a social phenomenon sui generis which would lose most of its explanatory power when reduced to rationalist logic. The first task in researching strong trust in international relations is to devise a theoretically sound definition of trust and, on that basis, theorize trust building as a succession of qualitatively separable stages. During this work, we will pay special attention to the ways in which Confidence Building Measures (CBMs) may be relevant for the trust building process. Second, we will construct a composite indicator for trust that depends on a) a computer assisted content analysis of official statements and b) a measurement of growing trust as it supersedes the need for treaty based control mechanisms in a dyad. We then validate this indicator in a structured, focussed comparison of the French-German, Polish-German and Russian-German relationships after the end of the cold war. In a third step, we present a theoretical account of the ways in which confidence building measures support the transformation from weakly to strongly trusting relationships between states. Ultimately, we will test this model in a number of comparative case studies.