Reclaiming Scholarly Publishing: National Policy, Diamond Open Access, and Canada's Path Forward
Bibliographic record
Abstract
This talk delivered on October 9th 2025, discussed Canada’s evolving open access landscape, with a focus on national policy shifts that have the potential to support digital research sovereignty and challenge the dominance of commercial scholarly publishing. It highlights Coalition Publica as a key example of a national open infrastructure supporting diamond open access in the social sciences and humanities, made possible through sustained multi-stakeholder engagement and collaboration. The role of diamond open access - a model that eliminates fees for authors and readers - in supporting multilingual publishing and promoting bibliodiversity is also examined. Drawing on the successes of this model, the talk will invite researchers to consider its applicability within STEM disciplines, particularly as funding agencies and institutions increasingly prioritize equitable, sustainable, and transparent access to publicly funded research.
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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 | 0.018 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.022 | 0.020 |
| Scholarly communication | 0.036 | 0.012 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".