The main goal of this contribution is to present a methodological innovation that expands the analytical potential of ethnographic research. As we know, under certain conditions ethnographic research is able to provide "fuzzy generalizations" (Bassey, 1999; Hammersley, 2001), which lead to the transferability of knowledge from one environment or context to others (Gomm, Hammersley, & Foster, 2000). Nonetheless, it is not easy to bridge the gap between individual characteristics that are made visible by the ethnographic approach and the understanding of a whole situation (i.e. actors and actants interacting in and with the given environment), which is needed in order to provide the research with applicable generalization. That is why we combined ethnographic techniques of gathering data with situational analysis (SA).
SA provides us with cartographic tools (Clarke, 2003; 2005) that allow the viewing of the researched environment together with its actors and actants as a dynamic system (Rockwell, 2005; Thelen & Smith, 1998). This is in accord with situational epistemology set by Dewey and developed by his followers (Dewey, 1992, lw.12; Johnson, 2007). SA thus enables researchers to describe a system in which there are no simple linear causal relationships, and yet it is possible to capture the laws and regularities given by the so-called "pragmatic cause" (Rockwell, 2005). This makes it possible to describe such a system and predict its future development without overly idealizing and reducing the initial analytical units of the entire system (quantitative methodology) or focusing on individual non-generalizable cases (qualitative methodology).
A dynamic system is characterized by: 1) the ongoing interactions of actors and actants with each other and with its environment, 2) the complexity of the interactions, and 3) feedback loops that permanently change the "essence" of relationships, and thus the "essence" of the very system elements (Thompson, 2007). The concurrence of the characteristics gives rise to the emergence of new system properties. However, the two-dimensional nature of the cartographic tools of SA does not allow the visualization and subsequent analysis of these emergent processes.
Relational maps allow researchers to find relationships between the basic units of analysis (the so-called "elements"). These relationships (so-called "mechanisms") explain how individual elements contribute to the character of the central element and how they, in this way, influence the whole situation (Clarke, 2005; 2014; Clarke & Montini, 2014). During the construction of the relational map, researchers are led to identify one element as central and in relation to it determine the mechanisms on the basis of which the researched situation is characterized.
This fact, however, leads to methodologically significant questions: How to properly determine the central element? Why this and not that element should be depicted as the central element? When we started to think about the very methodological principle on the basis of which SA is constructed, we realized that by using SA we cannot display the relationships among mechanisms. These relations are manifestations of emergent processes that play a key role in understanding any dynamic system. Thus, we realized that we are limited by the very two-dimensional principle of representation of SA. Inspired by Bachelard's insight into tool-knowledge continuity (1998), the theory of conceptual metaphor (Lakoff & Johnson, 1980; 1999), and the texts about other related themes (see below), we proposed an extension of SA with a three-dimensional representation. In our research, this allowed us to detect processes of de/synchronization.
Without this innovation, the process of de/synchronization would not be detected and no usable generalization could be presented. The proposed methodological innovation helps researchers doing ethnographic research to construct fuzzy generalizations that strengthen the credibility and applicability of their theories.