Diamond open access and open infrastructures have shaped the Canadian scholarly journal landscape since the start of the digital era
Bibliographic record
Abstract
Scholarly publishing involves multiple stakeholders having various types of interest. In Canada, the implication of universities, the presence of societies and the availability of governmental support for periodicals seem to have contributed to a rather diverse ecosystem of journals. This study presents in detail the current state of these journals, in addition to past trends and transformations during the 20th century and, in particular, the digital era. To this effect, we created a new dataset, including a total of 1265 journals, 943 of which appeared to be active today, specifically focusing on the supporting organizations behind the journals, the types of (open) access, disciplines, geographic origins, languages of publication and hosting platforms and tools. The main overarching traits across Canadian scholarly journals are an important presence of Diamond open access, which has been adopted by 61% of the journals, a predominance of the Social Sciences and Humanities disciplines and a scarce presence of the major commercial publishers. The digital era allowed for the development of open infrastructures, which contributed to the creation of a new generation of journals that massively adopted Diamond open access, often supported by university libraries. However, journal cessation also increased, especially among the recently founded journals. These results provide valuable insights for the design of tailored practices and policies that cater to the needs of different types of periodicals and that consider the evolving practices across the Canadian scholarly journal landscape
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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 | 0.012 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.023 | 0.067 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".