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The Rise of Partisanship and Super-Cooperators in the U.S. House of Representatives

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  • Clio Andris
  • David Lee
  • Marcus J Hamilton
  • Mauro Martino
  • Christian E Gunning
  • John Armistead Selden

Abstract

It is widely reported that partisanship in the United States Congress is at an historic high. Given that individuals are persuaded to follow party lines while having the opportunity and incentives to collaborate with members of the opposite party, our goal is to measure the extent to which legislators tend to form ideological relationships with members of the opposite party. We quantify the level of cooperation, or lack thereof, between Democrat and Republican Party members in the U.S. House of Representatives from 1949–2012. We define a network of over 5 million pairs of representatives, and compare the mutual agreement rates on legislative decisions between two distinct types of pairs: those from the same party and those formed of members from different parties. We find that despite short-term fluctuations, partisanship or non-cooperation in the U.S. Congress has been increasing exponentially for over 60 years with no sign of abating or reversing. Yet, a group of representatives continue to cooperate across party lines despite growing partisanship.

Suggested Citation

  • Clio Andris & David Lee & Marcus J Hamilton & Mauro Martino & Christian E Gunning & John Armistead Selden, 2015. "The Rise of Partisanship and Super-Cooperators in the U.S. House of Representatives," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-14, April.
    • Handle: RePEc:plo:pone00:0123507
    DOI: 10.1371/journal.pone.0123507
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    References listed on IDEAS

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    Cited by:

    1. Huremović, Kenan & Ozkes, Ali I., 2022. "Polarization in networks: Identification–alienation framework," Journal of Mathematical Economics, Elsevier, vol. 102(C).
    2. repec:cup:judgdm:v:15:y:2020:i:2:p:203-213 is not listed on IDEAS
    3. Neal, Zachary & Domagalski, Rachel & Yan, Xiaoqin, 2020. "Party Control as a Context for Homophily in Collaborations among US House Representatives, 1981 -- 2015," OSF Preprints qwdxs, Center for Open Science.
    4. Stone, Daniel, 2018. ""Unmotivated Bias" and Partisan Hostility: Empirical Evidence," SocArXiv hr5ba, Center for Open Science.
    5. Alina Sîrbu & Dino Pedreschi & Fosca Giannotti & János Kertész, 2019. "Algorithmic bias amplifies opinion fragmentation and polarization: A bounded confidence model," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-20, March.
    6. S. Glenn Baker & Niraj Patel & Curtis Von Gunten & K. D. Valentine & Laura D. Scherer, 2020. "Interpreting politically-charged numerical information: The influence of numeracy and problem difficulty on response accuracy," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(2), pages 203-213, March.
    7. Jonathan W. A. Ruff & Gregory Stelmach & Michael D. Jones, 2022. "Space for stories: legislative narratives and the establishment of the US Space Force," Policy Sciences, Springer;Society of Policy Sciences, vol. 55(3), pages 509-553, September.
    8. Xi Liu & Clio Andris & Bruce A Desmarais, 2019. "Migration and political polarization in the U.S.: An analysis of the county-level migration network," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-16, November.
    9. Andres Karjus & Christine Cuskley, 2024. "Evolving linguistic divergence on polarizing social media," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    10. Brownback, Andy & Novotny, Aaron, 2018. "Social desirability bias and polling errors in the 2016 presidential election," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 74(C), pages 38-56.
    11. Stone, Daniel F., 2019. "“Unmotivated bias” and partisan hostility: Empirical evidence," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 79(C), pages 12-26.

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