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        Medieval Manuscripts and the Computational Humanities

        Big Data, Scribes, and the “Paris Bible”

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        Author(s)
        Wrisley, David Joseph
        Guéville, Estelle
        Language
        English
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        Abstract
        This book examines the transformations in medieval studies—and the humanities more broadly—enabled by decades of digitization and advances in computational methods. Centring on the Paris Bible, a widely copied thirteenth- and fourteenth-century manuscript genre, we demonstrate how automated transcription produces scribal data at a scale once inaccessible, and how automation can support new approaches to localizing, dating, and contextualizing manuscripts. We argue that bringing machine learning and artificial intelligence to medieval studies not only requires re-centring expert human intelligence within computational systems, but also raises the question of the infrastructures needed for equitable, collaborative scholarship across the field. The book models how medieval studies might rethink interpretation, highlighting both the promise and risks of computational methods in manuscript research.
        URI
        https://library.oapen.org/handle/20.500.12657/111704
        Keywords
        Handwritten text recognition; Automated transcription; Academic crowdsourcing; Natural language processing; Materiality of manuscripts
        ISBN
        9781802704488, 9781802704488, 9781802702439, 9781802704495
        Publisher
        Arc Humanities Press
        Publisher website
        https://arc-humanities.org/
        Publication date and place
        Leeds, 2026
        Imprint
        Arc Humanities Press
        Classification
        Computer applications in the arts and humanities
        European history: medieval period, middle ages
        Literary studies: ancient, classical and medieval
        Historiography
        History: theory and methods
        European history
        Pages
        201
        Rights
        https://creativecommons.org/licenses/by-nc-nd/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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