Connecting Readers with Open Access Resources: The CUFTS Free! Open Access Collections Group.
Bibliographic record
Abstract
Libraries play an important role in disseminating knowledge. This paper presents an overview of the work of one library group, focused on collection of quality free and open access journals, and illustrates how libraries can be more effective in disseminating knowledge and connecting patrons with needed material by working collaboratively on open access and free collections. Also discussed are the few simple steps that publishers can take to facilitate dissemination of journal content through libraries – following standards such as OpenURL and/or DOI to provide for article-level linking, and providing title lists for download with the key metadata libraries need to include content in library collections, such as title, ISSN, fulltext start date, and journal URL. The CUFTS Free! Open Access Collections Group works collaboratively to connect library patrons with quality open access and free resources, ranging from the international Directory of Open Access Journals to locally developed lists such as Open Access Journals, Open Access Magazines, and Canadian Historic Newspapers. CUFTS is the knowledgebase (journal title lists) of reSearcher, a locally developed open source suite of resources. Through CUFTS, the open access and free journals collections are made available through a link resolving service (GODOT), A to Z journal lists, library catalogues and union databases. A file of MARC records for all of the titles is freely available to download, and downloadable spreadsheets are freely available for local collections as well, from http://www.eln.bc.ca/view.php?id=1129.
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.
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 | 0.017 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.021 | 0.023 |
| Open science | 0.006 | 0.019 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.293 | 0.311 |
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".