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The Eras Tour: Machine Learning for Dating Historical Texts from Greco-Roman Egypt

This paper introduces a machine learning approach to predicting the authorship dates of historical texts by using named entities — specifically, person and place names — as temporal markers.
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The Model is the Message: Modelling and the Future of Humanities Scholarship

In her review of Modelling Between Digital and Humanities: Thinking in Practice, Amanda Furiasse delves into the dynamic potential of modeling not just as a method, but as a transformative medium for humanities research, illuminating how modeling can empower scholars to adapt and thrive in an era of AI chatbots, VR simulations, and deepfakes.
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