As Russel King wrote ‘return is the great unwritten chapter of migration’ (2000). Accordingly, very little is known about how returning migrants experience their return, especially in the context of a post-socialist Central European country. The thesis thus presents an inquiry into the lived experiences of high-skilled Hungarian returning migrants. As theoretical engagement with return been fragmented and often marginal to migration theory, it presents a novel Integrated Theoretical Framework drawing on the insights of four pertinent areas of research, such as integration, re-integration, social networks and cultural identity. By combining the insights of the matrix of attachments, multi-dimensional re-embedding, social capital and support, and the Cultural Identity Model into a single framework, the thesis does not only address their individual shortcomings but enables a comprehensive analytical approach to understanding returnees’ experiences as a multi-faceted process within the broader migration cycle. In doing so, it applies a mixed-method social network approach, where it utilises personal network data and in-depth qualitative information from thirty-four returnees. As part of its data analysis, it combines thematic analysis qualitative analysis, fuzzy-set Qualitative Comparative Analysis, and descriptive social network measures with multi-level modelling techniques.
It finds that migrants’ experiences vary greatly from highly positive experiences to ambivalent or even hugely negative experiences. As the thesis shows, these experiences can be conceived as the result of migrants’ re-embedding process along five major dimensions, including their living standards, social, cultural, professional and political re-embedding, and that their social re-embedding plays a particularly important role. Moreover, returnees’ experiences are directly and positively linked to their social capital, which can be understood as the function of their positive and negative social ties, where negative ties have a disproportionately strong negative effect. As the multi-level social network analysis reveals, networks with several emotionally close ties to Hungarians who also reside in the country grants the most social capital for returnees. Additionally, based on their network compositions, returnees demonstrate five distinctive network trajectories throughout their migration cycle: transnationalism, ethnic maintenance, ethnification, host country attachment, and dispersion. These trajectories are underlined by different integration patterns and cultural identity changes, leading to markedly different re-embedding processes, social capital and consequently return experiences.
Dorottya is a final year PhD candidate in Sociology at the University of Manchester (expected graduation date 2020). She has a diverse educational background including Economics, Social Anthropology and Psychology from different international institutions, such as Central European University, the University of Glasgow and Maastricht University. Her work has so far centred on Social Network Analysis and migration. Most recently, her thesis has explored the lived experiences of high-skilled Hungarian returning migrants from a personal network perspective, using a mixed-methods approach. In general, she is interested in understanding the relationship between individual level outcomes and broader social structures. As of September 2020 she is a researcher at the ANET Lab of the Centre for Economic and Regional Studies, Hungary.