Three Experimental Approaches to Measure the Social Context Dependence of Prejudice Communication and Discriminatory Behavior

Empirical research on discrimination is faced with crucial problems stemming from the specific character of its object of study. In democratic societies the communication of prejudices and other forms of discriminatory behavior is considered socially undesirable and depends on situational factors such as whether a situation is considered private or whether a discriminatory consensus can be assumed. Regular surveys thus can only offer a blurred picture of the phenomenon. But also survey experiments intended to decrease the social desirability bias (SDB) so far failed in systematically implementing situational variables. This paper introduces three experimental approaches to improve the study of discrimination and other topics of social (un-)desirability. First, we argue in favor of cognitive context framing in surveys in order to operationalize the salience of situational norms. Second, factorial surveys offer a way to take situational contexts and substitute behavior into account. And third, choice experiments – a rather new method in sociology – offer a more valid method of measuring behavioral characteristics compared to simple items in surveys. All three approaches – which may be combined – are easy to implement in large-scale surveys. Results of empirical studies demonstrate the fruitfulness of each of these approaches.

Social Network Analysis and Qualitative Comparative Analysis: Their mutual benefit for the explanation of policy network structures

By switching the level of analysis and aggregating data from the micro-level of individual cases to the macro-level, quantitative data can be analysed within a more case-based approach. This paper presents such an approach in two steps: In a first step, it discusses the combination of Social Network Analysis (SNA) and Qualitative Comparative Analysis (QCA) in a sequential mixed-methods research design. In such a design, quantitative social network data on individual cases and their relations at the micro-level are used to describe the structure of the network that these cases constitute at the macro-level. Different network structures can then be compared by QCA. This strategy allows adding an element of potential causal explanation to SNA, while SNA-indicators allow for a systematic description of the cases to be compared by QCA. Because mixing methods can be a promising, but also a risky endeavour, the methodological part also discusses the possibility that underlying assumptions of both methods could clash. In a second step, the research design presented beforehand is applied to an empirical study of policy network structures in Swiss politics. Through a comparison of 11 policy networks, causal paths that lead to a conflictual or consensual policy network structure are identified and discussed. The analysis reveals that different theoretical factors matter and that multiple conjunctural causation is at work. Based on both the methodological discussion and the empirical application, it appears that a combination of SNA and QCA can represent a helpful methodological design for social science research and a possibility of using quantitative data with a more case-based approach.