Bibliographic record
Abstract
Citation (2015), "Contributors", Current Issues in Libraries, Information Science and Related Fields (Advances in Librarianship, Vol. 39), Emerald Group Publishing Limited, Bingley, p. ix. https://doi.org/10.1108/S0065-283020150000039005 Publisher: Emerald Group Publishing Limited Copyright © 2015 Emerald Group Publishing Limited Numbers in parentheses indicate the pages on which an author’s contribution begin. Denise A. D. Bedford (81) School of Library and Information Science, Kent State University, Kent, OH, USA Jennifer K. Donley (81) Heterick Memorial Library, Ohio Northern University, Ada, OH, USA Samir Hachani (115) School of Library Science, University of Algiers 2, Algiers, Algeria Mary Kandiuk (3) Scott Library, York University, Toronto, ON, Canada Nancy Lensenmayer (81) School of Library and Information Science, Kent State University, Kent, OH, USA Carla Teixeira Lopes (145) Faculty of Engineering, University of Porto, and Centre for Information Systems and Computer Graphics, INESC TEC Porto, Portugal Maureen L. Mackenzie (47) Division of Business, Molloy College, Rockville Centre, NY, USA Anamika Megwalu (185) Library, York College/City University of New York, Jamaica, NY, USA Lorri Mon (241) College of Communication & Information, Florida State University, Tallahassee, FL, USA Michael Perini (215) Fenwick Library, George Mason University, Fairfax, VA, USA Abigail Phillips (241) College of Communication & Information, Florida State University, Tallahassee, FL, USA Cristina Ribeiro (145) Centre for Information Systems and Computer Graphics, Institute for Systems and Computer Engineering of Porto, INESC TEC Porto, Portugal Beth Roszkowski (215) Arlington Campus Library, George Mason University, Arlington, VA, USA Harriet M. Sonne de Torrens (3) Department of Visual Studies and Library, University of Toronto at Mississauga, ON, Canada Book Chapters Current Issues in Libraries, Information Science and Related Fields Editorial Advisory Board Current Issues in Libraries, Information Science and Related Fields Copyright Page Contributors Preface Professional Issues Librarians in a Litigious Age and the Attack on Academic Freedom Educating Ethical Leaders for the Information Society: Adopting Babies from Business The Role of Librarians in a Knowledge Society: Valuing Our Intellectual Capital Assets Open Peer Review: Fast Forward for a New Science Transforming Services Effects of Terminology on Health Queries: An Analysis by User’s Health Literacy and Topic Familiarity Academic Social Networking: A Case Study on Users’ Information Behavior The Scholars’ Commons: Redefining Services and Spaces for Graduate Student Success The Social Library in the Virtual Branch: Serving Adults and Teens in Social Spaces Index
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.
How this classification was reachedexpand
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.022 | 0.001 |
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; both teacher heads agree on what is shown here.
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".