Updating and Cleaning ICPSR's State Legislative Election Returns Data and a Study of State Legislative Redistricting

更新和清理 ICPSR 的州立法选举结果数据以及州立法重新划分的研究

• 批准号: 0317924
• 负责人: Thomas Carsey
• 金额: $ 20.83万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-06-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0317924&HistoricalAwards=false
• 关键词: Updating; Cleaning; ICPSR; State; Legislative

Research on American legislative elections focuses predominantly on Congress, with far less attention given to state legislatures. This is unfortunate because the large number of state legislative elections, the variation across states in the character of legislative bodies and election rules, and the increased importance of states and state legislatures in policy making in the U.S. make state legislative elections especially well suited for testing theories about the nature of elections. Probably the greatest impediment to such research is the lack of readily accessible data about elections in the fifty states. Part I of the ICPSR data set, State Legislative Election Returns in the United States, 1968-1989 overcomes this obstacle, as it contains, among other things, a range of political and election outcome measures for each candidate running in every state legislative general election during the period. However, scholars have been unable to fully exploit these data because, for candidates for whom there are multiple observations, the name recorded frequently varies across observations (e.g. with and without a middle initial, with and without nickname, typographical errors). These errors make it impossible to reliably trace a particular candidate from one election to the next, thereby greatly limiting the utility of the data set. It has been estimated that among incumbents running in general elections for whom there were more than one observation included in this data set, 35% had at least one case in which their name was recorded differently - an error rate of 35%.The PIs, under a recent grant from NSF, have developed and implemented a procedure to "clean" the candidate names by creating an adjusted name variable that is consistent across multiple instances of the same candidate, and should have an error rate of 2% or less. The procedure includes a series of computer algorithms followed by the human review of records using a set of formal decision rules. This current investigation updates the State Legislative Elections Returns data through the 2002 elections and applies the name cleaning process to the extended data set. The result will be one seamless data set including information on every state legislative general election candidate from 1968 to2002 in which scholars can accurately trace the electoral history of each candidate. ICPSR has agreed to archive this updated and cleaned version of the data set which will include the original candidate name variable, the adjusted name variable, and all of the remaining twenty-seven substantive variables included in the original data set for the entire time period. To enhance the scholarly value of this data set, two companion data sets will be created - one containing numerous state-level variables for 1968-2002, andone including measures of district demographic characteristics for the 1992-2002 period.Several scholars have already expressed interest in using the enhanced State Legislative Election Returns data set. When completed, this data set will facilitate research on a diverse range of topics, including: partisan realignment in the South, the behavior and impact of minor party candidates, the determinants of electoral success of incumbents over the course of their careers, and the linkage between elections and the public policy choices of politicians. Importantly, for various reasons discussed in the proposal, systematic fifty-state analysis of such topics as the impact of term limits, the link betweenelections and roll call voting across states, and redistricting is feasible only if the data set is extended past 1989. Indeed, this research has a plan for the PIs to employ these data to study how the interaction of strategic candidates and legislative institutions affects the partisan and incumbency electoral pressures present in legislative redistricting.Beyond the basic research value of this research, the project has the potential for broader impacts by informing public debate on a broad range of issues, including redistricting, term limits, the incumbency advantage, and the operation of representative democracy in the American states.

对美国立法选举的研究主要集中在国会，而对州立法机构的关注要少得多。这是不幸的，因为美国州立法选举数量众多，各州立法机构的性质和选举规则存在差异，以及州和州立法机构在政策制定中的重要性日益增加，使得州立法选举特别适合检验有关选举性质的理论。此类研究的最大障碍可能是缺乏有关五十个州选举的易于获取的数据。 ICPSR 数据集的第一部分《1968-1989 年美国州立法选举结果》克服了这一障碍，因为它除其他外，还包含该期间参加各州立法大选的每位候选人的一系列政治和选举结果衡量标准。然而，学者们无法充分利用这些数据，因为对于有多个观察结果的候选人来说，记录的名字经常因观察结果而异（例如有或没有中间名首字母、有或没有昵称、印刷错误）。这些错误使得不可能从一次选举到下一次选举可靠地追踪特定候选人，从而极大地限制了数据集的实用性。 据估计，在参加大选的现任者中，如果该数据集中包含多个观察结果，则有 35% 的人至少有一次其姓名记录不同的情况 - 错误率为 35%。在 NSF 最近的一项资助下，PI 开发并实施了一种程序，通过创建在同一候选人的多个实例中一致的调整后的姓名变量来“清理”候选人姓名，错误率应为 2% 或 较少的。该程序包括一系列计算机算法，然后使用一组正式决策规则对记录进行人工审查。当前的调查更新了 2002 年选举期间的州立法选举结果数据，并将名称清理过程应用于扩展数据集。其结果将是一个无缝的数据集，其中包括 1968 年至 2002 年每位州立法机关大选候选人的信息，学者们可以在其中准确追踪每位候选人的选举历史。 ICPSR 已同意存档该数据集的更新和清理版本，其中将包括原始候选名称变量、调整后的名称变量以及整个时间段内原始数据集中包含的所有其余 27 个实质性变量。为了提高该数据集的学术价值，将创建两个配套数据集 - 一个包含 1968-2002 年期间的众多州级变量，另一个包含 1992-2002 年期间地区人口特征的衡量标准。一些学者已经表示有兴趣使用增强的州立法选举结果数据集。完成后，该数据集将促进对各种主题的研究，包括：南方的党派重组、小党候选人的行为和影响、现任者在其职业生涯中选举成功的决定因素，以及选举与政客公共政策选择之间的联系。重要的是，由于提案中讨论的各种原因，只有在数据集扩展到 1989 年之后，对诸如任期限制的影响、选举与跨州点名投票之间的联系以及选区重新划分等主题进行系统的 50 个州分析才是可行的。事实上，这项研究计划让 PI 使用这些数据来研究战略候选人和立法机构的相互作用如何影响州内存在的党派和在职选举压力。 立法选区重划。除了这项研究的基础研究价值外，该项目还可能通过为公众辩论提供更广泛的影响，包括选区重划、任期限制、现任优势以及美国各州代议制民主的运作等广泛问题。