Inter‐library loans and document delivery via EUCAT: a new PICA/OCLC initiative
Bibliographic record
Abstract
This paper explores the role of union catalogues in inter‐library loans and document delivery and how that role is changing to embrace virtual holdings and electronic document delivery. Figures from the Dutch National Union Catalogue (Nederlandse Centrale Catalogus, NCC) show that, contrary to expectations, physical loans are not decreasing but now comprise over a quarter of interlibrary loan activity. With direct user access, interlibrary loans have become unmediated and numbers of traditional loans and photocopies have steadily increased with a dramatic rise in electronic copy. International interlibrary loans pose technical and logistical problems for union catalogues. From a system viewpoint, it is necessary to integrate ILL systems, local library systems and to determine the end user’s ILL system and rights. EUCAT is an example of a federation of union catalogues. While the technical problems are more or less resolved, libraries still must determine the conditions for international co‐operation.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".