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Abstract(s)
Do politicians' relational traits predict their bipartisan voting behavior? In this paper, we empirically test and find that relational individual dispositions, namely attachment orientations and conformity to cultural norms, can predict the bipartisan voting behavior of politicians in the United States House of Representatives and Senate. We annotated politicians' tweets using a machine learning approach paired with archival resources to obtain politicians' home-state looseness-tightness culture scores. Anxiously-attached politicians were less likely to be bipartisan than avoidantly-attached individuals. Bipartisan voting behavior was less likely in politicians whose home state was less tolerant of deviation from cultural norms. We discuss these results and possible implications, such as the preemptive assessment of politicians' bipartisanship likelihood based on attachment and state cultural pressure to adhere to group norms.
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Keywords
Attachment Bipartisanship Machine learning Personality Tightness-looseness