Research on public segmentation methods needs to be replicated and expanded so that researchers understand the impact that scientific communication can have, for whom and in what contexts. A related question is how tailored messages designed to get people to take scientifically supported positions could influence their perception of scientists and scientific information. The diversity and origins of scientific controversies stand up to a simple classification and offer few proper comparisons. Much of what can be understood about these controversies comes from history, case studies, ethnography and other descriptive work. But despite their diversity and historical and cultural roots, scientific controversies often have three characteristics: various explanations have been proposed for polarization, which often surrounds scientific controversies. Such a statement, a reasoned argument, is discussed in Chapter 2. In this case, people tend not to accept statements contrary to their long-term views or values. A related explanation is that cultural prejudices – in particular preferences for equality against authority and for individualism in relation to the community – influence people`s perception of risk and related beliefs (z.B Kahan et al., 2009). According to this interpretation, individuals retain their identity as members of social groups that respect certain cultural values, as long as they do not take positions that are opposed to those they believe to be held by members of their group. However, much of the American public may have more moderate allegiances and views and therefore not be subject to this effect of group values.
In addition, a series of studies indicate that individual values predict their perception of risk (Dietz et al., 2007; Slimak and Dietz, 2006; Whitfield et al., 2009). This research needs to be expanded and integrated to determine its usefulness in predicting people`s reactions to different approaches to science communication. We also find that the conconnections of process/competence and interests/values of Americans  and this study, despite these studies with different analytical approaches, provide a fascinating basis for further research. Perhaps, for example, Americans in general – or people less known to science – merge the choice of methods (process) with competence, because they cannot imagine that several methods are competent: that is, there is only one way to study a particular scientific problem. Perhaps the German sample  did not show this confusion because the German education system as a whole or at a high level of education obtained by this sample was exposed to more or other information on this aspect of the scientific process. Finally, David Anzola studies the role of disagreement in the emergence of a new discipline of computer social science, which uses agent-based models to study social phenomena. As Anzola points out, one of the peculiarities of this new discipline is that it can be defined in relation to the use of a particular method, i.e. agent-based modeling, not on certain problems, theories or phenomena. As this method is not used in other disciplines that fall under social science, it creates a tension – a kind of disagreement – between it and its neighbouring fields.
However, Anzola describes how the agent-based modeling method was also considered an «average basis» – a kind of conciliatory position – between qualitative and quantitative methods in the social sciences. Although agent-based modellers have so far shifted to quantitative methods and have generally distanced themselves from the theoretical obligations that are generally contained in qualitative research (e.g. B radical constructivism and relativism), there is no fundamental reason why agent-based modeling should not cover both qualitative aspects and quantitative methods.