The purpose of the article is to point out the causal ladenness of empirical data in the social sciences. This is a kind of theory ladenness, representing implicit assumptions about the deterministic nature of political processes. The nonlinear and chaotic nature of social phenomena requires the collection of data not only about the current state of the system, but also about the evolution of the system. Using an example, we illustrate that the conclusions made on the basis of information about the final state can be very different from the conclusions made on the basis of monitoring the dynamics of the system. Low-importance factors can have big consequences in a chaotic case and, vice versa, there takes place fading of causality: considerable efforts can lead to more than modest results. For the successful management of political life, it is important to be able to identify the impacts that lead to great consequences.
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