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.

Citation: Andris C, Lee D, Hamilton MJ, Martino M, Gunning CE, Selden JA (2015) The Rise of Partisanship and Super-Cooperators in the U.S. House of Representatives. PLoS ONE 10(4): e0123507. https://doi.org/10.1371/journal.pone.0123507 Academic Editor: Rodrigo Huerta-Quintanilla, Cinvestav-Merida, MEXICO Received: March 28, 2014; Accepted: March 4, 2015; Published: April 21, 2015 Copyright: © 2015 Andris et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Data Availability: Congressional Roll Call Vote Data originally provided by the Office of the Clerk of the U.S. House of Representatives. Accessible through Govtrak at https://www.govtrack.us/congress/votes. Copyright Civic Impulse, LLC, (2014) Retrieved in bulk via instructions from https://www.govtrack.us/developers/data. Data on Congressional productivity and approval rate at: Ornstein N, Mann T, Malbin M, Rugg A (2013) Vital statistics on Congress. Washington, D.C.: The Brookings Institution. http://www.brookings.edu/research/reports/2013/07/vital-statistics-congress-mann-ornstein. Funding: This work was supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB), a component of the National Institutes of Health (NIH) (grant no T32EB009414) (to CEG), http://www.nibib.nih.gov/; John Templeton Foundation (grant no 15075) http://www.templeton.org/ (to CA, MJH); and National Defense Science and Engineering Graduate (NDSEG) Fellowship—Army Research Office (to CA). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. IBM Thomas J. Watson Research Center provided support in the form of a salary for author MM, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific role of this author is articulated in the ‘author contributions’ section. Competing interests: The authors have the following interests: At the time of the study, David Lee was a member of Senseable. Clio Andris and Mauro Martino were past members. Senseable's partners are a group of corporations, including AT&T, General Electric, Audi, ENEL, SNCF. Mauro Martino is employed by IBM Thomas J. Watson Research Center. There are no patents, products in development or marketed products to declare. This does not alter their adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.

Introduction Americans today are represented by political figures who struggle to cooperate across party lines at an unprecedented rate, resulting in high profile fiscal and policy battles, government shutdowns, and an inability to resolve problems or enact legislation that guides the nation’s domestic and foreign policy [1]. Partisanship has been attributed to a number of causes, including the stratifying wealth distribution of Americans [2]; boundary redistricting [3]; activist activity at primary elections [4]; changes in Congressional procedural rules [5]; political realignment in the American South [6]; the shift from electing moderate members to electing partisan members [7] movement by existing members towards ideological poles [8]; and an increasing political, pervasive media [9]. The individual representative’s role in facilitating partisanship is less clear. Party affiliation significantly shapes a legislator’s voting record [10], [11], so much that in some cases, a change in a legislator’s party affiliation results in an immediate and significant realignment of voting behavior towards the new party agenda [12]. This change is too rapid to be attributable to contemporaneous changes in constituent ideology, indicating a disconnection between the representative and his or her constituency. Party leaders also ensure obedience by offering incentives such as the prospect of assigning a member to a favored committee or promoting legislation crafted by the member to reach final voting stages, i.e. bringing legislation ‘to the floor’ [13]. As many have concluded [1], much is at stake with this type of party-driven arrangement. Despite party-level pressures, there are incentives for individual representatives to vote with members of the opposite party on issues that are specific to a district’s geography, such as aging populations, natural resource management, veterans’ affairs, or regional concerns [14]. Moreover, regardless of party affiliation, pairwise relationships may form as a result of social interactions such as sponsoring bills, interacting with lobbyists, creating trust networks for communication, sharing ideas, garnering support for initiatives, negotiating provisions and sharing one’s own sense of ethics and orthopraxy. Vote trading, also known as logrolling, is another incentive for cross-party cooperation [15]. Though difficult to quantify because vote trading discussions are not public information, these would result in increased inter-party cooperation on ideological votes. Given that individuals are persuaded to follow party lines [10–13], while having the opportunity and incentives to collaborate with members of the opposite party [14], [15], our goal is to measure the extent to which legislators tend to form ideological relationships with members of the opposite party. Specifically, we uncover cooperation rates between individual members of Congress, by leveraging a comprehensive dataset of each legislator’s roll call vote decisions in agreement or disagreement with each other legislator during a specific Congress. This process results in a network of Congressional representatives. Such network structures have been shown to predict future re-elections, define intra-Congressional communities and describe temporal dynamics of Congresses [16–21]. In studies that model Congressional representatives as nodes in a network, nodes are connected with an edge based on a given similarity between nodes, such as bill co-authorship or membership on the same committee [16–21]. We connect nodes with similar voting records on individual roll call votes, which represent similarities in ideology. Notably, the network method differs from prevailing legislator partisanship indexing methods [22–24] as the latter require the subjective quantification of each member on a single (liberal-to-conservative) linear scale (i.e. dimension). These dimensions are considered valuable because they temporally correlate with instances of landmark time periods and events in U.S. History [24]. Distinctive and groundbreaking, these dimensions are accepted as standard practice for quantifying polarization, as they serve as a reliable indicator of the political climate. Yet, above methods are best used to gauge the behavior of entire systems, and not well-suited for discovering interpersonal patterns of agreement forged by pairs of representatives. The network method is able to sidestep the following considerations of the current partisanship measurement tools [22–24]. First, when rating representatives in terms of a chosen vector of decisions deemed important, the index can be (perhaps incorrectly) manipulated to match correlation with events. The actual vote cocktail used to create the index, as well as how this value is transformed to a linear value is not clear to the layperson—perhaps nor to the seasoned social scientist. Also, polarization scale seems to have an arbitrary minimum and maximum that depends on the subjective choices of the creators. Secondly, when the difference between two representatives’ index values is used describe the ideological distance between a pair of representatives, as in [24], false similarities can occur. In this method, the index is centered at zero, signaling neutrality, and increasingly ‘strong’ members of one party (the other party) are increasing positive (negative) numbers. However, two moderate members can each have a zero index, but could actually disagree on every non-procedural issue. Thirdly, indexing methods are described in whole by aggregate measures, such as mean of members’ indexes as indicators of polarization [22–24] which obfuscate the role of the individual. Instead, network methods leverage raw, disaggregate data on each member’s voting behavior to uncover how cross-party pairs form organic relationships in Congress. More drawbacks to traditional index methods, with a focus on of their inability to detect groups, are astutely described in [21]. In this article, we first examine the decline of representatives who agree with representatives of the opposite political party on proposed legislation, and how this lack of collaborative voting reflects changes partisanship over the past 60 years (1949–2012). Our results show how the relative ease of cross-party cooperation in the late 1960s and early 1970s leads to the decoupling of the parties and the rise of a select few individuals who drive high rates of cross-party cooperation. We next discuss the correlation between decreased cooperation and decreasing legislative productivity in the 1990s and 2000s. We finally interpret findings in terms of overall trends in political climate, multiplicative growth processes, public behavior and the implications for the U.S. constituency.

Materials and Methods We use roll call vote data from the U.S. House of Representatives from 1949 (commencement of the 81st Congress) to 2012 (adjournment of 112nd Congress) (see Table 1) as provided by the United States Office of the Clerk of the U.S. House of Representatives via Govtrak [26] as described in [27], in a roll call vote, a representative chooses whether to respond (‘yay’/‘nay’) or abstain from voting on a bill or motion. Abstentions are relatively rare, and are counted as ‘nays’, as they do not support the legislation. Most abstentions come from members who are absent or unable to vote on the majority of votes, and have no network connections (i.e. they are not considered). Substantive roll call votes are proposed actions, bills and legislation regarding topics that produce new laws, such as veterans’ benefits, the budget and health insurance. Procedural roll call votes reflect votes on the organization and timing of the agenda [27], such as motioning to recess. We do not discriminate between these types although the latter are often unanimous votes and are largely excluded from the data set. PPT PowerPoint slide

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larger image TIFF original image Download: Table 1. Summary Statistics of Congressional Representatives and Voting Records. https://doi.org/10.1371/journal.pone.0123507.t001 For all B(n,2) possible pairs of representatives in a given Congress, we count the number of roll call votes where they voted the same way. We tally an agreement when a pair votes either ‘yay’/’yay’ or ‘nay’/’nay’. For example, Congressman A has voted similarly with Congressman B five times more often than with Congressman C in a session, giving the A-B relationship five times the weight of A-C. The result is a B(n,2)–cell, weighted, undirected graph of pair-wise relationships between representatives. Each pair is classified as either “same-party” (SP) if they are members of the same political party, or “cross-party” (CP) if one representative is Republican and the other Democrat. Independents are rare and are included as CP with all other non-Independents. Independents are not listed as super-cooperators due to their tendency to be in a cross-party pair with the majority of Congress. Representative absences are discarded. Agreements are not normalized by total possible votes or any another factor.

Discussion Our analysis shows that Congressional partisanship has been increasing exponentially for over 60 years, and has had negative effects on Congressional productivity. This is particularly apparent in the steady reduction of the number of bills introduced onto the floor, suggesting that the primary negative effect of increasing partisanship is a loss of Congressional innovation. But why is this pattern of increasing partisanship emerging so strongly? There are complex interactions that drive decision-making and pair-wise relationships in the House of Representatives. Though our data does not support a clear attribution of mechanism other than correlational associations with covariates, we find that polarization is part of a long-term exponential trend implying that non-cooperation multiplicatively breeds non-cooperation. In other words, today’s partisan atmosphere may not be a product of recent political splintering (such as the Southern Democrats [32] or the Republican Tea Party Group). Alternatively, such groups may have emerged from a growing shift from cooperation, while simultaneously contributing to the shift. Therefore, while it is incorrect to say that recent divisive political figures are responsible for increasing partisanship, they have actively contributed to it because these are the types of non-cooperative figures and factions that the multiplicative system selects. The exponential increase in non-cooperation shows no indication of slowing, or reversing, and so while Congress has steadily become more non-cooperative over the latter half of the 20th century, this trend seems likely to continue into the future. This increase in non-cooperation leads to an interesting electoral paradox. While U.S. voters have been selecting increasingly partisan representatives for 40 years, public opinion of the U.S. Congress has been steadily declining. This decline [30] suggests that voters cast their ballots on a local basis for increasingly partisan representatives whom they view as best representing their increasingly partisan concerns, leaving few if any moderate legislators to connect parties for a more cohesive Congress. Elected representatives are increasingly unable to cooperate at a national Congressional level but are re-elected at least 90% of the time, reflecting an evasion of collective responsibility. Voters might believe that highly partisan candidates will ‘tip the scale’ in one party’s favor. However, based on correlations shown here, a partisan candidate may lack cooperation needed to pass legislation. More moderate legislators may have a competitive advantage in negotiating for their party’s legislation. A fundamental reversal of increasing non-cooperation, over time, might require either a change in local ideological perspectives (resulting in a selective shift to fewer partisan representatives), or a fundamental change in how the electorate votes (from concerns focused on party issues to concerns focused on global effectiveness). Certainly current affairs do not seem to divide potential cooperators, as cross-party relationships peaked in arguably the most tumultuous period in recent U.S. history, marked with numerous political assassinations and Vietnam War and the resignation of President Nixon, as illustrated by others, such as [23–25]. It may be that decreased Congressional social interaction in Washington, D.C., combined with increased telecommunications and commuting to one’s home district, may hamper representatives’ ability cooperate. The United States is comprised of 435 unique Congressional districts, each with distinct physical geographies, economics, communities, cultures and political ideologies. At one time, these unique constituencies seemed to be represented by a distinct combination of ideologies from the Democratic and Republican Party. Formerly, legislators exhibited a mixture of ideals that resonated across party platforms, allowing each to forge a personal voting fingerprint that reflected the distinctive perspective of his or her unique district and constituency. Today, districts may remain as socio-economically and geographically unique as in the past, yet representatives have all but lost their personal voting records to complement their individualized constituencies. Instead, Americans today are represented by political figures whose ideological roll call voting record in the U.S. House of Representatives generally resembles one of only two types: either a Republican or a Democrat platform, with very little combination. What this unprecedented hyper partisanship will yield for the future of United States foreign and domestic policy is yet to be seen. This work was primarily performed at the Santa Fe Institute.

Acknowledgments The data reported in this paper are from Office of the Clerk of the U.S. House of Representatives, via Thomas Online Library of Congress as accessed through Govtrak. We thank the John Templeton Foundation, MIT Senseable City Lab, National Defense Science and Engineering Graduate (NDSEG) Fellowship, and the Rockefeller Institute. Authors acknowledge our four helpful reviewers and two academic editors, especially Dr. Rodrigo Huerta-Quintanilla. We would like to thank Thomas Ding and Wei Luo for assistance with data collection; Brian King, Luis M.A. Bettencourt and Chris Wood for discussions; and Nathan Frey, Leon Andris, and Deryck Holdsworth for advisory assistance with content editing.

Author Contributions Conceived and designed the experiments: CA MJH. Performed the experiments: CA CEG MJH. Analyzed the data: CA DL CEG MJH MM JAS. Contributed reagents/materials/analysis tools: DL CA. Wrote the paper: JAS CA DL MJH. Designed Interactive Website: MM.