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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.

The Aggregate Harmony Metric and a Statistical and Visual Contextualization of the Rehnquist Court: 50 Years of Data