Medieval Studies at the Newberry Library: A Report on New Approaches
Bibliographic record
Abstract
Medieval Studies at the Newberry Library:A Report on New Approaches Karen Ann Christianson, Christopher D. Fletcher, and Isabella Magni Medievalists today live in trying times. Alongside the inherent difficulties in studying the Middle Ages—learning languages, deciphering sources, developing research questions, etc.—faculty, graduate students, and undergraduates in all fields of medieval studies face daunting institutional challenges complicating the task of studying medieval cultures. Among others, professors are frequently forced to defend the value of medieval studies to skeptical administrations; graduate students face a troubling professional future with an increasingly constricting job market; and undergraduates interested in the Middle Ages find a shrinking number of medieval courses available as departments promote more general and global offerings. Understandably, these challenges also negatively affect the essential academic tasks of research, writing, and teaching medieval studies. Indeed, many departments, under pressure to draw in large numbers of undergraduates and to shorten graduate students' time in a PhD program, have discontinued offering the technical training necessary to study medieval cultures. Thus, students must learn vital skills (such as paleography, codicology, diplomatics, and prosopography) informally from individual professors, through self-study, or not at all. After graduation, scholars often find themselves teaching as adjunct instructors for little pay and bereft of the resources, including special collections, online journals, and databases, that were available to them at their previous institutions. No simple solution will fix the challenges facing medieval studies, but clearly academia itself cannot provide all the answers. Scholars and students both can benefit from institutions outside of universities that offer opportunities and resources for research, training, and collaboration that individual universities may not be able to offer on their own. The Newberry Library is one such institution. In this essay, we will provide a brief overview of how this independent research library [End Page 113] in Chicago helps to provide training and resources medievalists need to do their work in these challenging times. The Center for Renaissance Studies and the Newberry The Newberry Library owes its existence to Walter Loomis Newberry, a wealthy industrialist in Chicago. Newberry had long advocated for the creation of a great library in Chicago, and he left half of his estate for the creation of one should his daughters die without heirs. When the contingency in Newberry's will went into effect in the late nineteenth century, Chicago had already opened a public library, so the decision was made to establish a research library that would be free and open to the public. A few years later, after consultation with other recently established repositories in Chicago, the Newberry's leadership decided to focus collection development on humanities fields. Since the opening of the current library building in 1893, the Newberry has consistently offered its rich collection of around 1.5 million books, 15,000 linear feet of manuscripts, 500,000 maps, 200,000 pieces of sheet music, and other materials for the public's admiration and study.1 As the Newberry's collection grew over the years, the library became a desirable place for scholars of medieval studies to perform research. Its identity as a haven for medieval studies was strengthened by the foundation of the Center for Renaissance Studies (hereafter CRS) in 1979. CRS works with a consortium of institutions, originally consisting of five Chicago-area universities—the University of Chicago, Northwestern University, Loyola University Chicago, the University of Illinois at Chicago, and Northern Illinois University—and has always aimed to provide a place for students and faculty to take classes, work with original sources, and enjoy collaborations that would not have been possible at a given institution on an individual basis. Today, CRS has expanded significantly on these core principles, offering a variety of programming and resources for a consortium that now numbers around fifty universities from the United States, Canada, Europe, and the United Kingdom. At the same time, CRS also participates in the larger mission of the Newberry to promote the humanities and provide opportunities for the general public to engage with the library's rich collection of materials. What follows is a brief overview of how the center seeks to accomplish these goals through its programming and its digital resources. Programs for Graduate...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.019 | 0.015 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".