Assessing the collective wealth of Australian research libraries: measuring overlap using <i>WorldCat Collection Analysis</i>
Bibliographic record
Abstract
This paper reports the results of recent research examining the holdings of Australian research library collections recorded in the WorldCat database using OCLC WorldCat Collection Analysis software. The objectives of the research are: 1. To better understand the distribution of printed monographs amongst Australian research collections in order to assess the potential for enhanced collaboration in aspects of collection management. 2. To test the OCLC WorldCat Collection Analysis software in order to ascertain its value in comparing collection data based on the Australian research libraries subset of the WorldCat database. The collections compared are the National Library of Australia; University of Melbourne; Monash University, and CAVAL Archival and Research Materials Centre. The data record the extent of overlap between collections, and the prevalence and distribution of single copies. The paper refects on the use of WorldCat Collection Analysis software as a means of supporting the future management of Australian research collections. The research was undertaken as a pilot for a larger study.
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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 | 0.030 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.039 | 0.051 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".