An image from the site SCOTUS Notes.

A crowdsourcing project from two Midwestern universities plans to unlock some of the mysteries inside the U.S. Supreme Court's closed-door conferences.

The project, SCOTUS Notes, aims to “harness the power of citizen scientists or armchair scientists” to transcribe a collection of nearly 50,000 pages of the justices' handwritten conference notes on file at the Library of Congress, Washington and Lee School of Law and Yale Law School, according to political scientist Ryan Black of Michigan State University.

SCOTUS Notes launched on Feb. 13 and in its first six hours, 308 volunteers had signed on and completed just under 2,800 classifications of the notes, the first step before transcribing them, said Black, co-director of the project with Timothy Johnson, professor of political science and law at the University of Minnesota. Black and Johnson have done extensive research on the U.S. Supreme Court.

The initial focus of the project is on 12,600 pages of notes taken by Justices William Brennan Jr. and Harry Blackmun in cases decided between 1959 and 1994, and overlapping notes taken by Blackmun and Brennan between 1970 and 1990. Brennan served from 1956 to 1990, and Blackmun from 1970 to 1994.

But the “big barrier” to using the notes was “almost all of the time they're in the justices' handwriting,” he added. The answer to that barrier came when Johnson attended an open house at the University of Minnesota for the Zooniverse platform, the largest people-powered online research platform now supported by more than 1.5 million volunteers who help academic research teams with their projects.

“Tim called me and said, 'We can do this now,'” Black said. The two academics submitted a grant proposal to the National Science Foundation, which awarded them a three-year grant for the project using the Zooniverse platform. Although their funding ends in February 2019, they only have a small amount of data collection to complete, “loose ends” in the archives of Justice Lewis Powell Jr.

On the transcription side of the project, Black said many people will look at the same data to ensure accuracy. “There are multiple coders looking at the same sentence,” he said. “They've developed an algorithm that looks at how accurate an individual has been in the past and there will be cases where the algorithm says we need more people to look at an item.”

Black promises “sneak peaks” along the way. “When there are anniversaries of big cases, for example, we'll zoom in and look at what went on behind the scenes. It's an insane amount of fun.”

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