A Study of Collaborative Storage of Library Resources
Bibliographic record
Abstract
this report. His understanding of library issues and his wide perspective has enabled the study to readily synthesise the contribution of our literature. A further acknowledgement must be made of the thought and work of Lizanne Payne of the Washington Research Library Consortium. - 4 - Study of Collaborative Storage -- CAVAL Collaborative Solutions The UK context For at least a quarter of a century it has been recognized that libraries, particularly university libraries, cannot expand their collections indefinitely, nor obtain all their information needs from their own collections. An early report to deal with this issue in brutal practical terms was the Atkinson report in the 1970's, which introduced the concept of the "self -- renewing library". This proposed that for many university libraries, including research libraries, an optimal storage capacity should be identified, within which the library acquired material and disposed of it in equal measure. This proposition could be supported in the unique context of the UK where the BLDSC was available as a disposal destination and retention facility of last resort. However the proposition did not hold altogether. Collections continued to grow and successive new buildings, extensions and stores were created. All of the pre-1992 new universities (those created in the late 60's and early 70's) aspired to research excellence for which research collections are a necessity. The post 1992 new universities, whilst much more comfortable with the self-renewing concept, and emphasis on teaching collections, aspire also to research excellence, albeit much more selectively. Storage requirements have therefore steadily increased. As with other funding challenges, librarians have in their very professional way, looked towards collab...
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.021 | 0.031 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".