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1 to 8 of 8 Results
Nov 27, 2007
James H. Fowler; Sangick Jeon, 2007, "Replication data for: The Authority of Supreme Court Precedent", https://doi.org/10.7910/DVN/XMBQL6, Harvard Dataverse, V1, UNF:3:Suen5yCvzTQO0zq0nySNCg== [fileUNF]
We construct the complete network of 30,288 majority opinions written by the U.S. Supreme Court and the cases they cite from 1754 to 2002 in the United States Reports. Data from this network demonstrates quantitatively the evolution of the norm of stare decisis in the 19th Century and a significant deviation from this norm by the activist Warren Co...
Nov 27, 2007
James H. Fowler; Oleg Smirnov, 2007, "Replication data for: A Dynamic Calculus of Voting", https://doi.org/10.7910/DVN/AR8RLF, Harvard Dataverse, V1, UNF:3:90IeBTFmk2Oq/u/E/YG8Kw== [fileUNF]
We construct a decision-theoretic model of turnout, in which individuals maximize their subjective expected utility in a context of repeated elections. In the model a nonnegative signaling motivation to vote exists for all citizens, regardless of their ideology or beliefs about the closeness of the election, and is proportional to a citizen's exter...
Nov 27, 2007
James H. Fowler; Michael Laver, 2007, "Replication data for: A Tournament of Party Decision", https://doi.org/10.7910/DVN/MZPDXY, Harvard Dataverse, V1
In the spirit of Axelrod’s famous series of tournaments for strategies in the repeat-play prisoner’s dilemma, we conducted a “tournament of party decision rules” in a dynamic agent-based spatial model of party competition. A call was issued for researchers to submit rules for selecting party positions in a two-dimensional policy space. Each submitt...
Nov 27, 2007
James H. Fowler, 2007, "Replication data for: Habitual Voting and Behavioral Turnout", https://doi.org/10.7910/DVN/UMIPVS, Harvard Dataverse, V1
Bendor, Diermeier, and Ting (2003) develop a behavioral alternative to rational choice models of turnout. However, the assumption they make about the way individuals adjust their probability of voting biases their model towards their main result of significant turnout in large populations. Moreover, the assumption causes individuals to engage in ca...
Nov 27, 2007
James H. Fowler, 2007, "Replication data for: Turnout in a Small World", https://doi.org/10.7910/DVN/UMRZNM, Harvard Dataverse, V1, UNF:3:SKSt3wKOiZ9BI09TtCeHyA== [fileUNF]
This paper investigates between-voter interactions in a social network model of turnout. It shows that if 1) there is a small probability that voters imitate the behavior of one of their acquaintances, and 2) individuals are closely connected to others in a population (the “small-world” effect), then a single voting decision may affect dozens of ot...
Nov 27, 2007
James H. Fowler; Oleg Smirnov, 2007, "Replication data for: Dynamic Parties and Social Turnout: An Agent-Based Model", https://doi.org/10.7910/DVN/HAFAC1, Harvard Dataverse, V1
The authors develop an agent-based model of dynamic parties with social turnout built upon developments in different fields within social science. This model yields significant turnout, divergent platforms, and numerous results consistent with the rational calculus of voting model and the empirical literature on social turnout. In a simplified vers...
Nov 27, 2007
James H. Fowler, 2007, "Replication data for: Legislative Cosponsorship Networks in the U.S. House and Senate", https://doi.org/10.7910/DVN/O22JMY, Harvard Dataverse, V1, UNF:3:itEtOBEJ9KF5NEMmjLQPnQ== [fileUNF]
In the US House and Senate, each piece of legislation is sponsored by a unique legislator. In addition, legislators can publicly express support for a piece of legislation by cosponsoring it. The network of sponsors and cosponsors provides information about the underlying social networks among legislators. I use a number of statistics to describe t...
Nov 27, 2007
James H. Fowler, 2007, "Replication data for: Connecting the Congress: A Study of Cosponsorship Networks", https://doi.org/10.7910/DVN/JMZS8E, Harvard Dataverse, V1, UNF:3:itEtOBEJ9KF5NEMmjLQPnQ== [fileUNF]
Using large-scale network analysis I map the cosponsorship networks of all 280,000 pieces of legislation proposed in the U.S. House and Senate from 1973 to 2004. In these networks, a directional link can be drawn from each cosponsor of a piece of legislation to its sponsor. I use a number of statistics to describe these networks such as the quantit...
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