Assessing the collective wealth of Australian research libraries: measuring overlap using <i>WorldCat Collection Analysis</i>
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 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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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