Bibliographic record
Abstract
This presentation was delivered on Wednesday May 21st, 2025 as part of the COPPUL Scholarly Communications Skillshare. It provides an overview of the Canadian scholarly journal landscape and why domestic journals matter; the role library publishers play in supporting Diamond Open Access in Canada; and, finally, the types of support available to Canadian journals, along with a look ahead to upcoming policy changes that may impact them. Session description: Canada benefits from a uniquely not-for-profit scholarly journal publishing ecosystem, supported by a complex web of publishers, institutions, associations and service providers. Academic libraries occupy a dual position within this landscape. As publishing organizations, libraries partner with journals and editors on content production and creation, providing tools, infrastructure and services to support the publication of new scholarship. Libraries also have a long history as collectors and curators of Canadian journals, providing access to readers through our own collections and discovery tools, preserving content for the long term, and directing financial support to publishers in the form of licenses and other agreements. This session will explore some of the different facets of Canadian journal publishing, celebrate the strengths of this unique system, and consider the potential for its future.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.017 | 0.003 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.353 | 0.071 |
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".