Engaging Faculty and Reducing Costs by Leveraging Collections: A Pilot Project to Reduce Course Pack Use
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
INTRODUCTION Academic libraries have the privilege of serving many roles in the lives of their institutions. One role that is largely untapped is their ability to actively leverage their collections to support faculty teaching and to reduce student out-of-pocket costs by eliminating systemic double payment for course materials. DESCRIPTION OF PROGRAM/SERVICE This paper details a project by the Scholarly Communications and Copyright Office (SCCO) at the University of Toronto that aimed to reduce this systemic double payment by leveraging collections and electronic reserves to provide a new service, the Zero-to-Low Cost Courses. Building on existing relationships with faculty, SCCO staff reached out to potential candidates, identified library licensed materials in their printed course packs, and created digital course packs which students could use at no cost. NEXT STEPS This article shares the results of the project and explores next steps in using existing library resources to actively reduce student course costs.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.024 |
| Open science | 0.001 | 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