Measuring the Impact of Digital Collections
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
Assessing content use and reuse is a considerable challenge for gallery, library, archives, museum, and repository (GLAMR) digital library practitioners. While a number of digital object content use studies focus on quantitative approaches to assessment, including digital object downloads, views, and visits, little research has investigated the ways in which digital repository materials are utilized and repurposed. The Digital Content Reuse Assessment Framework Toolkit, or D-CRAFT, addresses some of these gaps by providing assessment methods, ethical considerations and guidelines, tutorials, and "how to" templates to assist practitioners in understanding how digital objects are used and reused by various audiences. The toolkit enhances and advances the typical digital library use assessment approaches. As such, this paper argues that D-CRAFT can play a critical role in assisting GLAMR digital library practitioners in reuse assessment data collection.
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 | 0.000 | 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 | 0.002 |
| 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