Abstract
In the last few decades, cross-border metropolitan regions (CBMRs) have been examined through the lens of binary prevailing network analysis, with substantial focus being placed on economy, innovations, and governance. However, the analysis of cultural networks is underrepresented in these contexts, although several voices have enquired about new concepts and practices for measuring spatial cultural networks and social proximities. This study was concerned with measuring cultural networks, as one step towards obtaining a deeper understanding of CBMRs. When focusing on cultural networks in border studies, it is necessary to understand: 1) how spatio-cultural networks can be conceptualised and measured from an interdisciplinary perspective; and 2) how cultural networks influence cross-border relations. Some of the literature has identified culture as the complex interrelation of values, artefacts, and behaviours, which presents multiple difficulties for analysing culture, per se. To analyse the influence of cultural networks in cross-border areas, this work took the Upper Rhine (UR), between the nation states of Germany, France, and Switzerland, as a case study. In the literature, this region is mainly referred to as being one coherent, integrated CBMR that shares similar dominant values. However, with regard to border cultural networks and national identities, this is empirically questionable. The UR region was analysed using two datasets, one quantitative and one qualitative. The analytical framework was based on the interlocking network model (INM) developed by Taylor (2001), which measures network and city centralities. Some adaptations were made to the INM to specifically analyse cultural networks in cross-border regions, giving rise to an ‘extended’ INM (EINM). Firstly, it was found that, although well-established cultural interrelations were identifiable in the UR cross-border region, a negative national border effect exists, leading to an uneven integration of German, Swiss and French cities into the cultural networks. Secondly, there was a significant difference between the INM and EINM, in terms of the number of relations and network centralities that could be captured, which led to different conclusions.
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