Accelerating the use of digital object identifiers (DOIs) in academic libraries
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
This paper explores the use of digital object identifiers (DOIs) in Canadian academic libraries. We analysed survey responses from 40 Canadian research organizations in order to understand the variables that accelerate or hamper the adoption of DOIs for digital research collections. Barriers to adoption include issues relating to technical barriers, lack of plugin integration, lack of dedicated technical staff, and the absence of institution-wide policy. Accelerants include the use of shared national research infrastructure, national funding to help reduce costs to libraries, and national consortia as technical liaisons and educators. Three priority areas for education include: guidance to help librarians decide when to apply a DOI to a resource; examples of metadata mappings for archival holdings and non-traditional formats; and the urgent need for support in maintenance planning for sustaining DOIs over the very long term.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.109 |
| Open science | 0.009 | 0.002 |
| Research integrity | 0.000 | 0.003 |
| 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