National Diamond Open Access funding models
Bibliographic record
Abstract
How can Diamond Open Access be funded? Three different approaches are presented in this conversation. The Finnish Federation of Learned Societies (TSV) hosts a platform with more than 150 learned society journals. For the last couple of years, they have been distributing funds specifically to cover the operating costs of under-financed Diamond journals. The grantees are required to not make any profit in addition to the governmental funds they get through TSV. In Canada, the centralized dissemination platform Érudit showcases more than 250 active, non-commercial scholarly journals. Thanks to government funding of scholarly journals, a thriving library publishing sector, and Érudit's own coordinated funding scheme, the majority of Canadian journals are by now Diamond. In the Netherlands, a special fund for flipping journals to Diamond Open Access has just closed its first call. The fund is designed to help medium to large size journals transition away from a commercial business model. The three interlocutors each have prominent roles in these funding schemes. Together they reflect upon the future of academic publishing and how the present landscape might look when viewed 150 years from now. Recording made April 8, 2025. First published online: May 28, 2025.
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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 | 0.040 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.027 | 0.024 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.044 | 0.010 |
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".