UC San Diego
Loss, Change, Adaptation: how people change when their lives do
- Author(s): Hobbs, William
- Advisor(s): Fowler, James H
- et al.
Many prominent theories in political science, and social science generally, argue that individuals are imprinted with behaviors and identities over the course of their lives. According to these theories, behaviors and identities persist due to internal, psychological consistency. Here, I argue that persistence in behavior, identity, and social interaction is often maintained by social networks, rather than individuals. Many day-to-day behaviors and identities would be constantly redefined and updated if there were reasons to do so. In other words, imprinting is often highly context specific, consistency in individuals is a property of stable social structures, and individuals can change very quickly when social networks around them allow or encourage it. The first paper in this dissertation ("Widowhood Effects in Voter Participation") studies why people are less likely to vote after their spouse dies. I show that a rapid, permanent drop in turnout is mostly not due to the trauma of the loss or a slowly declining interest in politics. Widows and widowers vote less because their spouse motivated them to vote. The second paper ("Partisan Attachment or Life Stability?") argues that partisan affiliations are stable in the United States electorate because day-to-day lives do not change very much. When lives do change, people reconsider their partisanship and are more likely to change it. A central argument in this paper is that age is associated with increasing partisan stability only because life stability increases with age. The last paper ("Plasticity in Human Social Networks") characterizes social network adaptations after the death of a friend. I show that mutual friends become permanently closer to each other after the shared loss, recovering the same volume of interactions that was lost from the death. Younger people tend to contribute more to recovery than older, but older people contribute equally when a loss was sudden and unexpected. The observed recovery occurs in distinct, overlapping patterns and is mathematically similar to shock responses in small-scale biological networks.