Charting variety, scope, and impact of open access diamond journals in various disciplines and regions: a survey-based observational study
Bibliographic record
Abstract
Purpose: The variety, scope, and impact of open access (OA) diamond journals across disciplines and regions from July 22 to September 11, 2020 were charted to characterize the current OA diamond landscape.Methods: The total number of diamond journals was estimated, including those outside the Directory of Open Access Journals (DOAJ). The distribution across regions, disciplines, and publisher types was described. The scope of journals in terms of authorship and readership was investigated. Information was collected on linguistic diversity, journal dynamics and life cycle, and their visibility in scholarly databases.Results: The number of OA diamond journals is estimated to be 29,000. OA diamond journals are estimated to publish 356,000 articles per year. The OA diamond sector is diverse in terms of regions (45% in Europe, 25% in Latin America, 16% in Asia, and 5% in the United States/Canada) and disciplines (60% humanities and social sciences, 22% sciences, and 17% medicine). More than 70% of OA diamond journals are published by university-owned publishers, including university presses. The majority of OA diamond journals are small, publishing fewer than 25 articles a year. English (1,210), Spanish (492), and French (342) are the most common languages of the main texts. Out of 1,619 journals, 1,025 (63.3%) are indexed in DOAJ, 492 (30.4%) in Scopus, and 321 (19.8%) in Web of Science.Conclusion: The patterns and trends reported herein provide insights into the diversity and importance of the OA diamond journal landscape and the accompanying opportunities and challenges in supporting this publishing model.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".