Nicolas Ceynowa

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Improving the readability of legislation is an important and unresolved problem. Recently, researchers have begun to apply legal informatics to this problem. This paper applies machine learning to predict the readability of sentences from legislation and regulations. A corpus of sentences from the United States Code and US Code of Federal Regulations was(More)
Over 2014, the Cornell University Legal Information Institute and the Australian National University worked with users of the Cornell LII site in a citizen science project to collect over 43,000 crowdsourced assessments of the readability of legal and other sentences. Readers (“citizen scientists”) on legislative pages of the LII site were asked to rate(More)
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