Roadmap for SSHRC Aid to Scholarly Journals: Adopting Best Practices in Diamond Open Access
Bibliographic record
Abstract
This road map is meant primarily for scholarly journals, with or without an embargo period/moving wall, that do not already use an open licence and that intend to comply with the criteria laid out in the 2025 SSHRC ASJ program, though any journal may find its guiding principles useful. In the summer of 2025, the Social Sciences and Humanities Research Council (SSHRC) announced its new Aid to Scholarly Journals (ASJ) program. The competition introduces new requirements for eligible journals for the next competition, scheduled for 2028. By 2028, SSHRC will require that all journals be made available in immediate open access without article processing charges (also known as diamond open access), have an open licence and be aligned with the criteria of the Directory of Open Access Journals (DOAJ) to be eligible for funding. Coalition Publica, as a partnership between Érudit and PKP working closely with university libraries, is committed to supporting journals in the transition to diamond open access and in adhering to best practices in digital publishing. We are pleased to provide this road map as one of the tools available to journals to undertake a transition to an open access business model and/or align the journal with best practices in open access 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 | 0.100 | 0.132 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.054 | 0.028 |
| Open science | 0.008 | 0.023 |
| Research integrity | 0.017 | 0.015 |
| Insufficient payload (model declined to judge) | 0.080 | 0.068 |
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".