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Description
Communities of Practice is funded by the Social Sciences and Humanities Research Council of Canada and explores how the multilingual urban bureaucracy of London — the world of Chaucer and his contemporaries — shaped late medieval literature. Bringing together linguistic, palaeographical, literary-historical, and computational methods, the project examines how networks of clerks employed in government offices contributed to the production, circulation, and transformation of literary texts between 1377 and 1471. By pairing innovative machine-learning techniques with traditional manuscript study, and making full use of the increase in digital access to archival documents, the project aims to move beyond linking single documents with individual clerks. Instead, it works towards a broader understanding of the distinctive scribal practices that arose in particular office communities and the role played by these scribal communities in the development of literary culture.
Scribal handwriting identification poses an unusual machine-learning problem: ground truth is largely unrecoverable. Few medieval scribes signed their work, and while palaeographers have attributed many documents with broad consensus, the contested cases, including some of the most consequential for literary history, resist resolution. Modern writer-identification methods achieve near-perfect accuracy on contemporary handwriting but degrade sharply on historical material. Meanwhile, digitisation has produced vast quantities of unlabelled manuscript images. In Communities of Practice we explore self-supervised representation learning to exploit this unlabelled data, with the goal of building tools that capture the “aspect” of writing, rather than opaque scores or classifications. The aim is not to settle attributions but to give scholars a new instrument with which to argue them.