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To what extent does the use of bipartisan language in state legislative campaigns predict a lawmaker's propensity to engage in bipartisan collaboration, and what might this mean for their legislative effectiveness? The study analyzes campaign materials for 11,038 legislators elected between 2006 and 2016 to identify candidates who utilize bipartisan rhetoric before their first term in office. Employing a word embedding model, the research navigates the complex linguistic landscape of political campaigns. This model leverages a neural network architecture to predict words in campaign statements based on contextual proximity. The analysis seeks to discern patterns of bipartisan messaging, evaluating both frequency and sincerity. This approach aims to determine if such rhetoric is a strategic tool for electoral success or reflects genuine bipartisan intentions. Post-election, the study further examines the behavior of elected lawmakers, investigating how campaign rhetoric aligns with legislative actions, explicitly focusing on cosponsorship behavior and its subsequent impact on legislators’ state legislative effectiveness scores (SLES).