Abstract: Love’s emergence as basis of marriage is a hallmark of modernity. Its compatibility with religious and traditional bases of marriage, however, is less understood. We explore the different criteria Iranians use to select their spouse as part of a broader effort to understand the complex relationships between love, religion and modernity. Love, we argue, does not mean the same thing to all, and its meaning is conditioned by the distinct historical and cultural frameworks in which it is embedded. Using a statistical technique called Latent Class Analysis, we analyze original survey data from an original online survey of more than 2,500 Iranians to examine these ideas. We find four distinct configurations of marital selection criteria, three of which include love. For some, love is the sole important criteria in marital decisions, for others love as a basis of marriage is tied to secularism and independence from familial opinions. For yet others, love as a basis of marriage is compatible with both seeking a pious mate and being religiously pious oneself. For individuals who adhere to traditional familial and gender norms, love does not figure as an important criterion, suggesting that patriarchal traditionalism, rather than religiosity may be an impediment to love-based marriages. These classes are not only demographically distinct but have implications for behavior, including who and how they love, whether they see God as loving, and the practices they engage in during courtship. We situate our findings in the context of Iranian cultural history, highlighting the forces that shaped these diverse forms of love, phenomenologically and institutionally.
Biography: Ramina is a Postdoctoral Prize Research Fellow in Sociology at Nuffield College, University of Oxford. Before joining Nuffield, Ramina received her PhD from the Department of Sociology at Princeton University, and her BA in Social Research and Public Policy at NYU Abu Dhabi. Ramina’s work spans the sociology of culture, social networks, biosociology and quantitative methods.