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

尽管联邦地区法院的重要性显而易见，但对这些法院的学术关注较少，特别是与对美国最高法院或美国上诉法院的研究相比。部分原因是现有数据库没有以最方便用户使用的格式传播，也因为它们缺乏重要的变数。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联合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不包括主持审判的法官的身份信息，也不包括案件当事人的信息。正因为如此，学者们无法在司法行为模型中纳入态度/思想和诉讼特征变量。本研究通过提供IDB样本的法官和诉讼信息来解决这一缺陷，从而使数据库对学者更有用，并为研究人员提供了利用IDB来审查联邦初审法院一级的决策的机会。这项研究将使用新的数据来检验和测试政党能力理论，该理论断言“富人”会领先。该研究将考察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/意识形态作出判决的条件。这项研究使用了双管齐下的策略来编码这些额外的信息。首先，计划在10年内，每年以4000件案件为对象，按年进行随机抽样，并利用Songer为上诉法院数据库开发的综合分类，收集有关诉讼类型的信息。由于这一初始分层随机样本很可能包括绝大多数在案件进入审判之前就已决定的程序性终止，因此该计划将编制每年1000例案件终止的额外“超额样本”。这将提供一个每年5000个观测值的数据集，跨越10年，包含程序终止（通过初始随机样本生成）和价值终止（基于初始随机样本和随后的超样本）。此外，该研究将在1995年至2015年的20年期间，每隔一年对5000例样本进行编码，而不是选择一个10年的时间段。这段时间跨度可以追踪四届总统任期内地方法院的制度变化。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事实提起诉讼的情况进行各种分析。该奖项反映了美国国家科学基金会的法定使命，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。

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.