EEBO and Us

Michael Gavin (270–78)

doi:10.14434/tc.v14i1.32860

Abstract

This essay responds to criticisms leveled against “How to Think About EEBO” (Gavin [2017] 2019). While my history of Early English Books Online was faulted for paying insufficient attention to the experiences of scholars using the collection, I argue that using digital tools for literary and bibliographical research can create a false sense of mastery that leaves scholars blind to the features of digital textuality that are most important historically and theoretically.

Highlights

“How to Think About Early English Books Online (EEBO)” was conceived and written as part of my larger effort to understand the growing role of computation in textual studies, a line of inquiry I have pursued elsewhere through articles that provide theoretical overviews and technical demonstrations of quantitative methods. (I’m one of those scholars. . .) quantification remains mired in controversy, making progress slow and difficult, and so I hoped, in my study of EEBO, to draw readers’ attention to fundamental questions about digital textuality while side-stepping anything that tends to provoke kneejerk hostility
I decided to suppress all prior commentary from book historians and others about new media and cybertext, choosing instead to go back to Charles Goldfarb, the inventor of Standard Generalized Markup Language (SGML), whose innovative reconceptualization of textuality continues to astonish for its originality and impact
In 1994, Sven Birkert’s Gutenberg Elegies: The Fate of Reading in an Electronic Age eloquently lamented the end of the print era

Summary

Introduction

Phrases like “from the codex to the computer” and “from Gutenberg to Google” became common tropes as scholars sought to fold new technologies into longer histories of textuality and reading. It’s a strange notion: Anything we don’t understand about computers can be dismissed as unfathomable, because the only vocabulary we need to speak authoritatively about computing comes from textual theory, and so to know about computers we need only to infer from our experience of using them to read and edit texts.

Results

Conclusion