“Access Versus Ownership” Revisited: The Quinnipiac University Libraries Short-Term Loan Project
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Challenged by a historically small monographs collection, a considerable growth in the number of students and academic programs, and faced with space limitations in the stacks, Quinnipiac University librarians began their large-scale investment in e-books in January 2011. Initially, we subscribed to ebrary’s Academic Complete collection. That same year, we began a conversation with EBL and its then Vice President of Sales, Dr. David Swords. It was our desire to compare a subscription approach with a patron-driven acquisitions strategy as we further examined the place of e-books in our libraries. Initially, in 2012, we offered EBL titles published from 2010–2012. Yet, questions remained around the purchase of e-books even when our patrons used EBL titles. An e-book, used but once or twice took up no shelf space, but it represented a purchase—funds spent. In ownership, it also represented a unit that required care; feeding; and, quite possibly, weeding. Discussions with our colleagues at Fairfield University about their short-term loan (STL) strategy intrigued us, and we are indebted to them for sharing data, observations, and issues encountered. In October 2012, Quinnipiac’s Arnold Bernhard Library expanded its own STL initiative, making available the entire EBL catalog and adhering almost completely to STL activity. That is, we bought almost no e-books but made more than 300,000 academic titles available to our patrons. Charles Getchell, former Director of the Bernhard Library, Quinnipiac; June DeGennaro, Collection Management Librarian, Quinnipiac; and David Swords, EBL-Ebook Library/ProQuest will share with you key elements of the planning, implementation, and outcome assessment of this full-fledged STL program at Quinnipiac University. Surprises, discoveries, and future plans will be shared as well. We remain intrigued, as, at present, only three known academic libraries in North America have this valuable access strategy in place.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it