How assessment websites of academic libraries convey information and show value
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
Purpose As libraries are required to become more accountable and demonstrate that they are meeting performance metrics, an assessment website can be a means for providing data for evidence-based decision making and an important indicator of how a library interacts with its constituents. The purpose of this paper is to share the results of a review of websites of academic libraries from four countries, including the UK, Canada, Australia and the USA. Design/methodology/approach The academic library websites included in the sample were selected from the Canadian Association of Research Libraries, Research Libraries of the United Kingdom, Council of Australian University Libraries, Historically Black College & Universities Library Alliance, Association of Research Libraries and American Indian Higher Education Consortium. The websites were evaluated according to the absence or presence of nine predetermined characteristics related to assessment. Findings It was discovered that “one size does not fit all” and found several innovative ways institutions are listening to their constituents and making improvements to help users succeed in their academic studies, research and creative endeavors. Research limitations/implications Only a sample of academic libraries from each of the four countries were analyzed. Additionally, some of the academic libraries were using password protected intranets unavailable for public access. The influences of institutional history and country-specific practices also became compelling factors during the analysis. Originality/value This paper seeks to broaden the factors for what is thought of as academic library assessment with the addition of qualitative and contextual considerations.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.023 |
| 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