University of Alberta Library & Open Access Monographs
Bibliographic record
Abstract
In this presentation Sarah Chomyc, Collection Strategies Librarian at the University of Alberta Library, discusses institutional approaches to assessing and supporting open access (OA) initiatives. This presentation was delivered as part of the workshop: “Bridging Altruism To Strategy in OA Book Publishing: How Libraries Can Close Funding Gaps to Support a Bibliodiverse Global Shared Collection” (1 May 2024, online). The workshop was organised by Lyrasis in collaboration with Open Book Futures (a Copim Community research project, co-funded by Arcadia and the Research England Development fund). The workshop explored how libraries can better respond to the strategic and practical challenges of supporting bibliodiverse futures for open access (OA) book publishing. The event focused in particular on the new and distinct strategies required to connect the dots between different aspects of library workflows, from ensuring quality of content, to collections development, to rendering content – and especially open access content – discoverable and available for users. More information on the workshop is available here: https://copim.pubpub.org/pub/workshop-bridging-altruism-to-strategy-in-oa-book-publishing
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.400 | 0.122 |
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".