Disentangling Active and Passive Cosponsorship in the U.S. Congress

• URL: http://arxiv.org/abs/2205.09674v1
• Date: Thu, 19 May 2022 16:33:46 GMT
• Title: Disentangling Active and Passive Cosponsorship in the U.S. Congress
• Authors: Giuseppe Russo, Christoph Gote, Laurence Brandenberger, Sophia Schlosser, and Frank Schweitzer
• Abstract summary: In the U.S. Congress, legislators can use active and passive cosponsorship to support bills. We show that these two types of cosponsorship are driven by two different motivations: the backing of political colleagues and the backing of the bill's content. We develop anRGC+N based model that learns legislator representations from bill texts and speech transcripts.
• Score: 0.09236074230806579
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In the U.S. Congress, legislators can use active and passive cosponsorship to support bills. We show that these two types of cosponsorship are driven by two different motivations: the backing of political colleagues and the backing of the bill's content. To this end, we develop an Encoder+RGCN based model that learns legislator representations from bill texts and speech transcripts. These representations predict active and passive cosponsorship with an F1-score of 0.88. Applying our representations to predict voting decisions, we show that they are interpretable and generalize to unseen tasks.

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