Collaborative Research: Building a Multi-User Database of District Court Decisions

合作研究：建立地方法院判决的多用户数据库

• 批准号: 1920991
• 负责人: Kirk Randazzo
• 金额: $ 23.95万
• 依托单位: University of South Carolina at Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1920991&HistoricalAwards=false
• 关键词: Collaborative; Research; Building; Multi; User

Despite the obvious importance of the Federal District Courts, less scholarly attention has been directed to these courts, particularly as compared to studies of the U.S. Supreme Court or the U.S. Courts of Appeal. In part this is because available databases have not been disseminated in the most user-friendly format and because they lack important variables. Foremost among these underutilized datasets is the Integrated Database (IDB) of federal district court decisions distributed by the Federal Judicial Center in conjunction with the Administrative Office of the United States Courts. However, even though the IDB has been publicly available since the 1980s, it is almost never used by social scientists studying the courts because IDB does not contain information on the identity of the judges presiding over trials nor on the litigants of the case. Because of this, scholars are unable to incorporate attitudinal/ideological and litigant characteristic variables in models of judicial behavior. This research addresses this shortcoming by supplying judge and litigant information for a sample of the IDB, thus rendering the database more useful to scholars and providing researchers with the opportunity to utilize the IDB to examine decision making at the federal trial court level. The research will use the new data to examine and test party capability theory, which asserts that the "haves" come out ahead. The research will examine the conditions under which federal district court judges render decisions according to the characteristics and resources of the litigants and the attitude/ideology of the judge. The research uses a two-prong strategy to code this additional information. Initially, the plan will code a random sample stratified by year of 4000 cases per year for ten years, to collect information regarding litigant type using the comprehensive categories developed by Songer for the Courts of Appeals database. Because this initial stratified random sample is likely to include a vast majority of procedural terminations decided before the case goes to trial, the plan will code an additional "over-sample" of 1000 merits terminations per year. This will provide a dataset of 5000 observations per year, across ten separate years, containing both procedural terminations (generated through the initial random sample) and merits terminations (based on the initial random sample and subsequent over-sample). Moreover, instead of picking a single ten-year period, the research will code the sample of 5000 cases from every other year over a 20-year period, 1995 through 2015. This time span allows the tracking of institutional changes to the district courts across four presidential administrations. Collecting this information will allow scholars to conduct various analyses on the preliminary motions and evidentiary motions potentially leading to settlements rather than trials, as well as the situations in which the merits of a dispute are litigated in a trial.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

尽管联邦地区法院的重要性显而易见，但与美国最高法院或美国上诉法院的研究相比，对这些法院的学术关注较少。部分原因是现有的数据库没有以最方便用户的格式传播，而且缺乏重要的变量。在这些未充分利用的数据集中，最重要的是联邦司法中心与美国法院行政办公室共同分发的联邦地区法院判决综合数据库。然而，尽管IDB自1980年代以来一直公开提供，但研究法院的社会科学家几乎从未使用过它，因为IDB不包含关于主持审判的法官身份或案件诉讼当事人的信息。正因为如此，学者们无法将态度/意识形态和诉讼特征变量纳入司法行为模型。本研究解决了这一缺点，提供法官和诉讼信息的IDB的样本，从而使数据库更有用的学者和研究人员有机会利用IDB审查决策在联邦审判法院一级。这项研究将使用新的数据来检查和测试政党能力理论，该理论认为“有”的人走在前面。这项研究将审查联邦地区法院法官根据诉讼当事人的特点和资源以及法官的态度/意识形态作出裁决的条件。这项研究使用了一种双管齐下的策略来编码这些额外的信息。最初，该计划将对每年4000起案件的随机样本进行编码，为期10年，使用Songer为上诉法院数据库开发的综合类别收集有关诉讼类型的信息。由于这一最初的分层随机抽样很可能包括绝大多数在案件进入审判之前决定的程序性终止，该计划将每年额外编码1000个优点终止的“过度抽样”。 这将提供一个每年5000个观察结果的数据集，跨越10个独立的年份，包含程序性终止（通过初始随机样本生成）和依据终止（基于初始随机样本和随后的过度样本）。此外，该研究将从1995年到2015年的20年期间每隔一年对5000例病例进行编码，而不是选择一个单一的十年期。这一时间跨度使得能够跟踪四个总统行政当局的地区法院的体制变化。通过收集这些信息，学者们可以对可能导致和解而不是审判的初步动议和证据动议，以及在审判中对争议的是非曲直进行诉讼的情况进行各种分析。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。