Allyship in academia is critical for creating inclusive communities that are welcoming to all students, but the perception of its benefits and challenges can vary depending on a number of factors. This session will explore perspectives of allyship in academia by bringing together a diverse group of faculty and students who can share a wide range of experiences and insights, and aims to facilitate a discussion among all attendees that leads to an exchange of ideas, the strengthening of our community, and progress toward our common goal of inclusion in computing.

We introduce the task of book structure labeling: segmenting and assigning a fixed category (such as TABLE OF CONTENTS, PREFACE, INDEX) to the document structure of printed books.We manually annotate the page-level structural categories for a large dataset totaling 294,816 pages in 1,055 books evenly sampled from 1750-1922, and present empirical results comparing the performance of several classes of models.The best-performing model, a bidirectional LSTM with rich features, achieves an overall accuracy of 95.8 and a class-balanced macro F-score of 71.4.