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: 1921042
• 负责人: Robert Howard
• 金额: $ 13.22万
• 依托单位: Georgia State University Research Foundation, Inc.
• 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=1921042&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.

尽管联邦地方法院的重要性显而易见，但学术界对这些法院的关注较少，特别是与美国最高法院或美国上诉法院的研究相比。部分原因是可用的数据库尚未以最用户友好的格式传播，并且它们缺乏重要的变量。这些未充分利用的数据集中最重要的是联邦地区法院判决的综合数据库（IDB），由联邦司法中心与美国法院行政办公室共同分发。然而，尽管 IDB 自 20 世纪 80 年代以来就已公开，但研究法院的社会科学家几乎从未使用过它，因为 IDB 不包含有关主持审判的法官或案件当事人身份的信息。因此，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中。本研究通过提供 IDB 样本的法官和诉讼当事人信息来解决这一缺陷，从而使该数据库对学者更有用，并为研究人员提供利用 IDB 审查联邦初审法院一级决策的机会。该研究将利用新数据来检验和检验政党能力理论，该理论认为“富人”领先。该研究将探讨联邦地方法院法官根据诉讼当事人的特征和资源以及法官的态度/意识形态做出裁决的条件。该研究使用双管齐下的策略来编码这些附加信息。最初，该计划将在十年内对每年 4000 起案件进行分层的随机样本进行编码，以使用 Songer 为上诉法院数据库开发的综合类别收集有关诉讼人类型的信息。由于这个初始分层随机样本可能包括案件审理前决定的绝大多数程序性终止，因此该计划将每年额外编码 1000 名择优终止的“过度抽样”。 这将提供跨越十年的每年 5000 个观测值的数据集，其中包含程序终止（通过初始随机样本生成）和优点终止（基于初始随机样本和随后的过度采样）。此外，该研究不是选择一个单一的十年期，而是对 1995 年至 2015 年这 20 年期间每隔一年的 5000 个案件进行样本编码。这个时间跨度允许跟踪四届总统政府期间地方法院的机构变化。收集这些信息将使学者们能够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智力价值和更广泛的影响审查标准进行评估，被认为值得支持。