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。部分原因是因为可用的数据库尚未以最用户友好的格式传播，并且因为它们缺乏重要的变量。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发行的联邦地方法院裁决的综合数据库（IDB）。但是，即使自1980年代以来，IDB已公开可用，但研究法院的社会科学家几乎从未使用过，因为IDB不包含有关主持审判或案件诉讼人的法官身份的信息。因此，学者无法在司法行为模型中纳入态度/意识形态和诉讼特征变量。这项研究通过向IDB样本提供法官和诉讼信息来解决这一缺点，从而使数据库对学者更有用，并为研究人员提供了利用IDB在联邦初审法院级别检查决策的机会。该研究将使用新数据来检查和测试方能力理论，该理论断言“遗之重要”是领先的。该研究将研究联邦地方法院法官根据诉讼人的特征和资源以及法官的态度/意识形态做出决定的条件。该研究使用两项策略来编码此其他信息。最初，该计划将使用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，每年按每年4000个案例分层的随机样本进行编码，以收集有关诉讼类型的信息。由于此初始分层的随机样本可能包括在案件进行审判之前确定的绝大多数程序终止，因此该计划每年将编码额外的1000名优点终止的“过度样本”。 这将提供一个每年5000个观测值的数据集，包括十个单独的年份，其中包含过程终止（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时样本）。此外，该研究没有选择一个十年的时间，而是在1995年至2015年的20年内每隔一年的5000例案件进行编码。这个时间范围允许跟踪四个总统政府的地方法院的机构变更。收集这些信息将使学者能够对初步动议和证据动议进行各种分析，这可能导致定居点而不是试验，以及在试验中诉讼诉讼的情况的情况。该奖项反映了NSF的法定任务，并通过评估了基金会的智力效果，并通过评估了基金会和广泛的影响。