{"title":"The Aggregate Harmony Metric and a Statistical and Visual Contextualization of the Rehnquist Court: 50 Years of Data","authors":"Peter A. Hook","doi":"10.2139/SSRN.987301","DOIUrl":null,"url":null,"abstract":"This article contains aggregated data from fifty years of the annual matrixes of justice inter-agreement for particular Supreme Court terms published by the Harvard Law Review (1956 to 2005 terms). Aggregating how often any two justices sided together on cases for a particular term relative to the amount of cases the two justices heard together allows one to derive a measure of the particular term that reflects the relative amount of agreement or disagreement for the term. This new metric, called the Aggregate Harmony Metric, allows for comparative benchmarks. For instance, the 2005 term, with an aggregate agreement of 70%, was the high water mark for agreement amongst the Court over the past 50 terms - significantly higher than the mean of 60% and the low of 50% (1970 term).Additionally, co-voting data is visualized spatially for teaching purposes. Spatial visualizations quickly convey to the viewer which justices are often in agreement, which are seldom in agreement, and which justices are outliers. In addition to providing new visualizations, the article surveys past visualizations and reporting of co-voting data. Another benefit of aggregating the Harvard Law Review's statistics for all 50 Terms (1956-2005) is the ability to see the highest and lowest voting agreement percentages between any two justices over the span of the dataset. The article contains charts of these voting superlatives. For instance, Warren and Marshall are at a 50 year high for those having decided more than 100 cases together (88%). Similarly, the polemic nature of Justice Douglas is evident in the fact that he is one of the Justices in each of the first six, lowest voting agreement percentages. Furthermore, the status of O'Connor and, to a lesser extent Kennedy, as swing voters is visually portrayed using the network graphic metaphor with nodes and edges. Metrics and visualizations go a long way towards making the tacit knowledge of expert scholars of the Court available to both law students and the general public. Data mining, statistical processing, and visualization tools with built-in layout algorithms make this possible. The field of information visualization as it relates to legal topics is still in its infancy and ripe for substantial growth.","PeriodicalId":81001,"journal":{"name":"Constitutional commentary","volume":"24 1","pages":"221-264"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Constitutional commentary","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/SSRN.987301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This article contains aggregated data from fifty years of the annual matrixes of justice inter-agreement for particular Supreme Court terms published by the Harvard Law Review (1956 to 2005 terms). Aggregating how often any two justices sided together on cases for a particular term relative to the amount of cases the two justices heard together allows one to derive a measure of the particular term that reflects the relative amount of agreement or disagreement for the term. This new metric, called the Aggregate Harmony Metric, allows for comparative benchmarks. For instance, the 2005 term, with an aggregate agreement of 70%, was the high water mark for agreement amongst the Court over the past 50 terms - significantly higher than the mean of 60% and the low of 50% (1970 term).Additionally, co-voting data is visualized spatially for teaching purposes. Spatial visualizations quickly convey to the viewer which justices are often in agreement, which are seldom in agreement, and which justices are outliers. In addition to providing new visualizations, the article surveys past visualizations and reporting of co-voting data. Another benefit of aggregating the Harvard Law Review's statistics for all 50 Terms (1956-2005) is the ability to see the highest and lowest voting agreement percentages between any two justices over the span of the dataset. The article contains charts of these voting superlatives. For instance, Warren and Marshall are at a 50 year high for those having decided more than 100 cases together (88%). Similarly, the polemic nature of Justice Douglas is evident in the fact that he is one of the Justices in each of the first six, lowest voting agreement percentages. Furthermore, the status of O'Connor and, to a lesser extent Kennedy, as swing voters is visually portrayed using the network graphic metaphor with nodes and edges. Metrics and visualizations go a long way towards making the tacit knowledge of expert scholars of the Court available to both law students and the general public. Data mining, statistical processing, and visualization tools with built-in layout algorithms make this possible. The field of information visualization as it relates to legal topics is still in its infancy and ripe for substantial growth.
本文包含了《哈佛法律评论》(Harvard Law Review)发表的50年来最高法院特定条款的年度司法协议矩阵(1956年至2005年条款)的汇总数据。将任何两位大法官在某一特定任期内站在一起的次数与这两位大法官一起审理的案件数量相结合,可以得出对特定任期的衡量标准,该标准反映了该任期内一致或不一致的相对数量。这个新的度量标准被称为“综合和谐度量”,允许进行比较基准。例如,在2005年的任期内,法院达成一致意见的总数达到70%,是过去50个任期内达成一致意见的最高水平,大大高于60%的平均值和50%的低点(1970年任期)。此外,为了教学目的,共同投票数据在空间上可视化。空间可视化可以迅速向观众传达哪些法官经常意见一致,哪些法官很少意见一致,哪些法官是异常值。除了提供新的可视化之外,本文还调查了过去的可视化和共同投票数据的报告。汇总《哈佛法律评论》所有50个任期(1956-2005)的统计数据的另一个好处是,能够看到在数据集的跨度内,任何两位大法官之间最高和最低的投票一致百分比。这篇文章包含了这些投票的图表。例如,沃伦和马歇尔共同裁决100多起案件的比例达到了50年来的最高水平(88%)。同样,道格拉斯法官的争论本质也很明显,因为他是前六名中投票赞成率最低的法官之一。此外,奥康纳和肯尼迪(在较小程度上)作为摇摆选民的地位,使用带有节点和边缘的网络图形隐喻,在视觉上被描绘出来。计量标准和可视化对使法院专家学者的隐性知识向法律学生和公众开放大有帮助。内置布局算法的数据挖掘、统计处理和可视化工具使这成为可能。与法律主题相关的信息可视化领域仍处于起步阶段,需要大量发展。