Re-learning the Commons, From Conceptual Overview to Case Study [Plenary Speaker]
Bibliographic record
Abstract
The early conceptual description of the Commons model as “a new framework for service delivery in academic libraries” has by now been validated by real-world practical experiences on well over a hundred campuses in Canada, the U.S., Europe, and the Pacific Rim. A few critics over the years have repeatedly predicted that a series of new technologies would “threaten,” “derail,” or “doom” the Commons model (laptops, netbooks, PDA’s, tablets, smartphones, "the cloud" ….each of these, it was claimed in succession, would render the Commons model obsolete, irrelevant, or deserted). Instead, the Learning Commons has shown itself to be a dynamic focal point of organizational adaptation and growth, enthusiastic student use and acceptance, increased collaboration across a spectrum of instructional support and pedagogical incubation, and creative integration of knowledge media and library service delivery.This keynote address begins with an overview of recent assessments from several campuses that reveal these general trends, and then delves into a longer, more detailed Case Study of current exciting development projects at the University of North Carolina, Charlotte, designed to emphasize the role of the LC in enhancing student learning, engagement, retention and success.Donald Beagle, Director of Library Services, Belmont Abbey College, Belmont, NCBarbara Tierney, Head of Research and Information Services for the Information Commons, Department of the J. Murrey Atkins Library, University of North Carolina at Charlotte. Presentation co-written by Donald Beagle and Barbara Tierney. Presented by Barbara Tierney.
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 | 0.004 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".