Recalibrating the scope of scholarly publishing: A modest step in a vast decolonization process
Bibliographic record
Abstract
Abstract By analyzing 25,671 journals largely absent from common journal counts, as well as Web of Science and Scopus, this study demonstrates that scholarly communication is more of a global endeavor than is commonly credited. These journals, employing the open-source publishing platform Open Journal Systems (OJS), have published 5.8 million items; they are in 136 countries, with 79.9% in the Global South and 84.2% following the OA diamond model (charging neither reader nor author). A substantial proportion of journals operate in more than one language (48.3%), with research published in 60 languages (led by English, Indonesian, Spanish, and Portuguese). The journals are distributed across the social sciences (45.9%), STEM (40.3%), and the humanities (13.8%). For all their geographic, linguistic, and disciplinary diversity, 1.2% are indexed in the Web of Science and 5.7% in Scopus. On the other hand, 1.0% are found in Cabell’s Predatory Reports, and 1.4% show up in Beall’s (2021) questionable list. This paper seeks to both contribute to and historically situate the expanded scale and diversity of scholarly publishing in the hope that this recognition may assist humankind in taking full advantage of what is increasingly a global research enterprise.
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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 | 0.111 | 0.247 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".