The 18th World Congress of Jewish Studies

The Edition of Keter Shem Ṭov by means of the tool LERA (Locate, Explore, Retrace and Apprehend complex text variants)

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Keter Shem Ṭov (“The Crown of the Good Name”) is a Hebrew treatise composed in the thirteenth century and is one of the most important introductory texts into Kabbalah. The text has a long history of transmission, was discussed in Jewish as well as Christian circles, and is testifying in about 100 different manuscripts.
We will present an interdisciplinary project (see https://kabbalaheditions.org) that aims to elaborate a hybrid edition of various textual witnesses of Keter Shem Ṭov. We will display LERA (https://lera.uzi.uni-halle.de), an interactive digital collation tool to analyze differences and similarities among multiple witnesses of a text. The software has been extended for the edition of Keter Shem Ṭov, e.g., by the representation and processing of Hebrew, the algorithmic handling of dozens of text witnesses, the improved analysis of large structural rearrangements of a text as well as the visualization of small textual variants in a horizontal score (“score-synopsis”).
Through the comparison and analysis of the transcribed manuscripts with the tools provided by LERA, we detected the existence of several versions of Keter Shem Ṭov as well as their stemmatological relationship. Already the oldest manuscripts attest a close interdependency with another treatise called Divre Menaḥem sharing a couple of sections with Keter Shem Ṭov. New results concern the existence of a mixed version of both treatises and an abridged version of Keter Shem Ṭov. A textual unit at the end of Keter Shem Ṭov is actually a commentary on Job 28 known in a more elaborated version as part of the introduction to the Commentary of Song of Songs by Ezra of Gerona as well as an anonymous paraphrase integrated in the Commentary on Job by Nahmanides. Our lecture will discuss the question of how to face the editorial problems involved and to apply the digital solutions of LERA.

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