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Abstract

This Article introduces a novel empirical method for measuring judicial importance beyond traditional metrics, such as citation counts, which often undervalue decisions that shape legal practice without generating extensive case law. Drawing on techniques from computational text analysis, it proposes linguistic shifts—systematic changes in the length, language, and structure of legal documents—as an alternative proxy for a judicial opinion’s legal significance.

The Article applies this method to a case study involving Blackboard, Inc. v. Desire2Learn, Inc., 574 F.3d 1371 (Fed. Cir. 2009), a Federal Circuit decision that has received relatively little attention under conventional citation-based measures. By programmatically analyzing more than 300 patents filed before and after Blackboard, the Article demonstrates that Blackboard triggered a measurable linguistic shift in how patent prosecutors draft the very type of patents at issue. These findings demonstrate that Blackboard significantly shaped practitioner behavior despite its low citation count.

More broadly, the Article demonstrates that computational analysis of linguistic shifts can serve as a scalable, doctrinally agnostic, and empirically verifiable framework for assessing judicial influence. By capturing changes in legal practice beyond the litigation process, this approach expands the scope of judicial influence to include legal actors and behaviors that are otherwise invisible to conventional metrics.

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