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We introduce Computer Assisted Legal Linguistics (CAL2) as a semi-automated method to “make sense” of legal discourse by systematically analyzing large collections of legal texts. Such digital corpora have been increasingly used in computational linguistics in recent years, as part of a quantitative research strategy designed to complement (rather than supplant) the more qualitative methods used hitherto. This use of statistical algorithms to analyze large bodies of text meets with an increasing demand by lawyers for empirical data and the recent turn towards evidence-based jurisprudence. Together, these research strands open exciting avenues for research and for developing useful IT tools to support legal decision-making, as we exemplify using our reference corpus of about 1 billion tokens from the language of German jurisprudence and legal academia.
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