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Partisan Webs: Information Exchange and Party Networks
Published online by Cambridge University Press: 01 July 2009
Abstract
What is a party? This article presents the argument that rmal party apparatus is only one part of an extended network of interest groups, media, other advocacy organizations and candidates. The authors have measured a portion of this network in the United States systematically by tracking lists of names transferred between political organizations. Two distinct and polarized networks are revealed, which correspond to a more liberal Democratic group and a more conservative Republican group. Formal party organizations, like the Democratic National Committee and the Republican National Committee, tend to receive information within their respective networks, which suggests that other groups serve to funnel information towards the formal party.
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References
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3 A 527 is a tax-exempt organization that influences elections but does not directly advocate for or against a specific candidate, and therefore is not regulated by the Federal Elections Commission. The term refers to Section 527 of the US Internal Revenue Code, which governs political organizations.
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14 James Q. Wilson, The Amateur Democrat: Club Politics in Three Cities (Chicago: University of Chicago Press, 1962).
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16 For example, Barbara Sinclair, in Legislators, Leaders, and Lawmaking, reports that congressional party leaders work closely with allied interest groups to set the legislative agenda, whip legislators and win votes.
17 Schattschneider, The Semisovereign People.
18 The Republican National Committee recently altered its website to change the designation of various non-profit, tax-exempt organizations with which it is normally associated. These groups, including the American Enterprise Institute, the Heritage Foundation, and the Leadership Institute, had been listed as ‘GOP Groups’ but have been re-labelled as ‘Other Organizations’. See John Byrne, ‘After Raw Story article, Republican National Committee modifies website’, Raw Story, 16 January 2006.
19 Jeffrey L. Pasley, The Tyranny of Editors: Newspaper Politics in the Early American Republic (Charlottesville: University of Virginia Press, 2001).
20 Anthony Downs, An Economic Theory of Democracy (New York: Harper & Row, 1957), p. 25.
21 Joseph A. Schlesinger, Ambition and Politics: Political Careers in the United States (Chicago: Rand McNally, 1966), p. 6.
22 E. E. Schattschneider, Party Government (Westport, Conn.: Greenwood Press, 1942), p. 35.
23 Richard M. Skinner, ‘Do 527’s Add up to a Party? Thinking About the “Shadows” of Politics’, The Forum, 3 (2005), Article 5.
24 Mildred A. Schwartz, The Party Network: The Robust Organization of Illinois Republicans (Madison: University of Wisconsin Press, 1990).
25 Jonathan Bernstein, ‘The Expanded Party in American Politics’ (doctoral dissertation, University of California–Berkeley, 1999); Joseph W. Doherty, ‘Organized by Competition: Candidate–Consultant Networks in California Legislative Campaigns’ (paper presented at the Annual Meeting of the American Political Science Association, Washington, D.C., 2005).
26 Marty Cohen, David Karol, Hans Noel and John Zaller, The Party Decides: Presidential Nominations Before and After Reform (Chicago: University of Chicago Press, 2008).
27 Casey Byrne Knudsen Dominguez, ‘Before the Primary: Party Participation in Congressional Nominating Processes’ (doctoral dissertation, University of California–Berkeley, 2005).
28 See Jonathan Bernstein, ‘Network Research, Factions, and the Next Agenda’ (presented at the Ray C. Bliss Institute of Applied Politics Conference on the State of the Parties: 2004 and Beyond, Akron, Ohio, 2005).
29 Party networks are mapped by analysing the donations of party-loyal donors in Casey B. K. Dominguez, ‘Groups and the Party Coalitions: A Network Analysis of Overlapping Donor Lists’ (paper presented at the Annual Meeting of the American Political Science Association, Washington, D.C. 2005).
30 Larry Sabato, The Rise of Political Consultants: New Ways of Winning Elections (New York: Basic Books, 1981).
31 Schlozman and Tierney conducted a similar experiment on a much smaller scale. They had a child join several organizations, and three of those groups generated mail from other organizations. The new groups were ideologically similar to the original three. For details, see Kay Lehman Schlozman and John T. Tierney, Organized Interests and American Democracy (New York: Harper & Row, 1986).
32 Steve Kaufman, personal communication with authors, 22 September 2005.
33 Some list owners may waive rental fees to aid affiliated groups, but we cannot observe such behaviour.
34 Former Rep. Ben Nighthorse Campbell (R-Colorado) recently complained that Rep. Bob Beauprez (R-Colorado) was soliciting from Campbell’s old donor list for his 2006 gubernatorial campaign without permission. As Campbell said, ‘Part of the problem is if the word is out that they’re using your list, there’s a sort of subtle insinuation that you’re endorsing the candidate – and I’m not’ (Lynn Bartels, ‘Donor list flare-up’, Rocky Mountain News, 8 October 2005).
35 Theoretically, the argument follows in higher dimensions. Empirically, we look at a single ideological dimension.
36 McCarty, Poole and Rosenthal, Polarized America, pp. 139–63. See especially Figure 5–4.
37 The authors go on to show that the groups whose mean recipient is moderate are still more likely to donate to extreme members on both sides of the aisle. This, we think, is consistent with the notion that some groups view themselves as in the middle of the ideological spectrum. It is less consistent, however, with our claim that groups are unwilling to work with members from the other party. Presumably, the access motive for contributions trumps party considerations at least at the campaign donation stage.
38 McConnell v. Federal Election Commission, 540 U.S. 92 (2003), opinion of Stevens and O’Connor for the Court, at 148.
39 The antonym of a directed relationship is a ‘symmetric’ relationship, in which the relationship between two actors is necessarily equivalent for both. ‘Neighbour’, for example, is a symmetric relationship; if A lives next door to B, then B lives next to A.
40 This software is available at http://www.analytictech.com/ucinet.htm. Readers interested in learning more about social network analysis may begin with Stanley Wasserman and Katherine Faust, Social Network Analysis: Methods and Applications (New York: Cambridge University Press, 1994); and Robert A. Hanneman and Mark Riddle, Introduction to Social Network Methods (Riverside: University of California–Riverside, 2005).
41 There are a several other SNA techniques for studying sub-groups within a society. These include a number of standards for identifying cliques that are too restrictive for our data, identifying components of a society (all our cases are either connected in one group or completely isolated), or the clustering coefficient. The clustering coefficient measures the extent to which a society is broken into smaller groups. Our data are highly clustered (0.140) relative to their density (0.0053). See Hanneman and Riddle, Introduction to Social Network Methods, esp. chaps 8 and 11.
42 Hanneman and Riddle, Introduction to Social Network Methods, chap. 4.
43 When we divided the nodes into four or five factions no new groups were classified into the fourth or fifth faction. When groups are classified into two factions all the points in the ‘Other’ faction are lumped with the Republican EPN. Dean’s disconnect from the rest of the Democratic network is discussed below.
44 The transfers from Democratic EPN nodes to Republican EPN nodes were: UNICEF to Veterans of Foreign Wars, NY Review of Books to Easton Press, New Republic to The Week, and Americans United for Separation of Church and State to Commentary magazine. The Republican EPN to Democratic EPN transfers were National Review to Mother Jones and The Economist, and Weekly Standard to The Economist and Wall Street Journal.
45 David Krackhardt and Robert Stern, ‘Informal Networks and Organizational Crises: An Experimental Simulation’, Social Psychology Quarterly, 51 (1988), 123–40.
46 To calculate this statistic we ignored the direction of the ties.
47 See Wasserman and Faust, Social Network Analysis. There are three basic notions of centrality: degree, closeness (i.e. being near many actors), and betweenness (being the linchpin for links between other actors) (see Hanneman and Riddle, Introduction to Social Network Methods). For directed data, scholars sometimes consider it ‘prestigious’ to receive many ties and ‘influential’ to initiate many ties. In this presentation we are agnostic about whether it is better to give than receive.
48 Wasserman and Faust, Social Network Analysis, p. 200. We used ucinet’s ‘Closeness’ algorithm with reciprocal geodesic distances. There are several other measures of centrality, including eigenvector centrality and power indexes, but we found them unsuited to our sparse network of directed relationships.
49 Dominguez, ‘Groups and the Party Coalitions’.
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