17. UK Research Reserve – the journey of de-duplication continues
Bibliographic record
Abstract
As technologies continue to help libraries innovate how they operate, both librarians and users want to provide/receive new services and in ways that hadn’t been possible in the past. It represents great opportunities in many areas, but in reality, changes come with challenges. One of the key challenges is the shortage of space as research libraries have accumulated a lot of items over the years and often the solution is to acquire more and bigger buildings to keep them. To tackle this issue, libraries in the UK work together to identify scarce material for retention and release space by disposing of widely available holdings. By deaccessioning through the UK Research Reserve (UKRR), participating libraries have the confidence that they are making informed decisions and are ensured that research material is preserved and remains accessible (one copy would be kept by UKRR’s partner, the British Library [BL], as the access copy and two copies would be retained by member libraries as preservation copies.) This membership model is essential as it determines if an item is available through the BL’s document delivery services and whether it is scarce or not. This model has worked well and has helped release about 85km of shelf space during UKRR Phase 2. However, this membership model also means that only about 18% of Higher Education Institutions (HEIs) in the UK have access to UKRR services. With financial support from the Higher Education Funding Council for England (HEFCE), UKRR aims to open its door to all, within and beyond the HE sector, and invite any library who wishes to de-duplicate their holdings to join the programme. To be able to do so, it is crucial to identify new homes for preservation copies if offering libraries are not committed to retain for the community. By introducing a new role (Preservation Library), the new model offers all libraries an opportunity to dispose of material responsibly and in an informed manner. More importantly, it also ensures that at a time of constant change, research resources that the UK has accumulated for centuries remain accessible to the research community. Through the poster event, we want to tell the UKRR story and its transition so far. We also want to share thoughts with delegates and learn from their experience.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.031 | 0.028 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.013 | 0.009 |
| Insufficient payload (model declined to judge) | 0.114 | 0.102 |
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".