Convergence and Collaboration of Campus Information Services
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
Illustrations Preface Chapter 1: Introduction Peter Hernon and Ronald R. Powell Chapter 2: Innovation is an Ongoing Process: Collaboration at the University of California, Irvine Carol Ann Hughes Chapter 3: Sowing an Old Field with a New Crop: Collaborative Services of Libraries and Other Campus Units Richard W. Meyer and Tyler O. Walters Chapter 4: From Isolation to Engagement: Strategy, Structure, and Process Barbara J. Kriigel and Timothy F. Richards Chapter 5: Convergence and Collaboration in Information Services at the University of Calgary Darlene Warren Chapter 6: The Library as Model of Integrated Student-Centered Academic Support Enterprise Jay Schafer and Anne C. Moore Chapter 7: The University of Georgia Student Learning Center Florence E. King, Carla Wilson Buss, Nadine Cohen, Deborah Stanley, and Elizabeth White Chapter 8: From Faction to Fusion: The Columbia University Libraries as Information Services Enterprise James Neal Chapter 9: Libraries and Convergence at Yale Alice Prochaska Chapter 10: The Poetry Center at Suffolk University Fred Marchant and Robert E. Dugan Chapter 11: Collaborative Initiatives to Deliver Agricultural Information Barbara Hutchison, Jeanne Pfander, and George Ruyle Chapter 12: Other Perspectives and Concluding Thoughts Peter Hernon, Ronald R. Powell, and Amy F. Fyn Bibliography Index About the Editors and Contributors
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.022 |
| Open science | 0.000 | 0.000 |
| 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