  This article focuses on the transcription of medieval manuscripts. Whereas
problems of transcription have long interested medievalists, few workable
options in the era of printed editions were available besides normalisation.
The automation of this process, known as handwritten text recognition (HTR),
has made new kinds of digital text creation possible, but also has foregrounded
the necessity of theorising transcription in our scholarly practices. We
reflect here on different notions of transcription against the backdrop of
changing text technologies. Moreover, drawing on our own research on medieval
Latin Bibles, we present general guidelines for customizing transcription
schemes, arguing that they must be designed with specific research questions
and scholarly end use in mind. Since we are particularly interested in the
scribal contribution to the production of codices, our transcription guidelines
aim to capture abbreviations and orthographic variation between different
textual witnesses for downstream machine learning tasks. In the final section
of the article, we discuss a few examples of how the HTR-created transcriptions
allow us to address new questions at scale in medieval manuscripts, such as
textual variance across witnesses, the prediction of a change in scribal hands
within a single manuscript as well as the profiling of individual and regional
scribal characteristics.
