Bibliographic record
Abstract
This exploratory study seeks to gather preliminary information about the roles that academic librarians in the United States (US) and Canada play in the Scholarship of Teaching and Learning (SoTL) work on their campuses. It also provides insight into how librarians at US Carnegie Research 1 (R1) classified universities and U15 Group of Canadian Universities (U15) participate in SoTL, to discover ways by which these librarians might grow these roles, as well as their understanding of SoTL expertise, to better support students. Data was collected through an internationally distributed survey. The authors used thematic analysis along with descriptive statistics to examine how academic librarians participated in SoTL practices as consultants, developers, partners, and scholars. Results from this study expand upon prior research on the role of librarians in this field of study and examines how barriers can be broken down to improve the working relationships between teaching faculty and librarians at research intensive universities to enhance student learning.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.022 | 0.017 |
| Scholarly communication | 0.019 | 0.018 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".