Collaborative Research: Individual-Level Analysis of Supreme Court Justices: A Modification to the United States Supreme Court Judicial Databases

合作研究：最高法院法官的个人层面分析：美国最高法院司法数据库的修改

• 批准号: 9910535
• 负责人: Harold Spaeth
• 金额: $ 6.76万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-01-15 至 2001-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9910535&HistoricalAwards=false
• 关键词: Collaborative; Research; Individual; Level; Analysis

Much is to be said for judicial databases that treat a court's decision as the unit of analysis-as is evidenced by the widespread use over the past twelve years of the two NSF-Supported U.S. Supreme Court Judicial Databases. Indeed, almost no empirical studies fail to avail themselves of the data contained in these two databases. However, neither allows for research pertaining to the behavior of the individual justices, as distinct from the aggregate analysis of the Court's decisions/outcomes. This shortcoming is a major limitation to understanding the behavior of the justices. Empirical studies of the behavior of the individual justices arguably provide the most fruitful route to understanding judicial behavior. With the databases so transformed, scholars will be able to efficiently investigate such theoretically important matters as individual-level analysis of voting behavior, models predicting and explaining dissent or concurrence, opinion assignment, as well as any other question that requires choice among several options using independent variables that vary both by justice and by case -- i.e., those amenable to the use of conditional logit analysis or hierarchical models.Recently formulated procedures allow the two databases to be "flipped" so that their focus becomes the justice rather than the case. Such transformations require systematic coding of the individual justice's voting and opinion behavior that does not pertain to the Court's decisions; i.e., the 4500 special opinions (dissents and concurrences) and the 11,000 votes represented by the opinions that the justices wrote and cast between 1946 and 1999. The result will be two complementary user-friendly databases, paralleling the existing ones, but increased in size by a factor of approximately ten, extending across a period from 1946 to the end of the currently existing Rehnquist Court.

对于将法院判决作为分析单位的司法数据库来说，还有很多话要说，这一点可以从过去12年来两个由NSF支持的美国最高法院司法数据库的广泛使用中得到证明。事实上，几乎所有的实证研究都利用了这两个数据库中的数据。然而，两者都不允许对个别法官的行为进行研究，这与对最高法院判决/结果的综合分析不同。这一缺陷是理解大法官行为的一个主要限制。 对法官个人行为的实证研究可以说是理解司法行为最有成效的途径。有了这样的数据库，学者们将能够有效地研究这些理论上重要的问题，如投票行为的个人层面分析，预测和解释异议或赞同的模型，意见分配，以及任何其他需要在几个选项中选择的问题，这些选项使用因正义和案例而异的自变量-即，最近制定的程序允许两个数据库“翻转”，使其重点成为正义，而不是案件。 这种转变需要对大法官个人的投票和意见行为进行系统编码，而这些行为与最高法院的判决无关;即，1946年至1999年间法官撰写和投出的4500份特别意见（异议和同意）和11，000张选票。 其结果将是两个互补的用户友好的数据库，与现有的数据库平行，但规模增加了约10倍，从1946年到目前存在的阿恩奎斯特法院结束。