Bibliographic record
Abstract
This study assessed characteristics of publishers who published 2010 open access (OA) journals indexed in Scopus. Publishers were categorized into six types; professional, society, university, scholar/researcher, government, and other organizations. Type of publisher was broken down by number of journals/articles published in 2010, funding model, location, discipline and whether the journal was born or converted to OA. Universities and societies accounted for 50% of the journals and 43% of the articles published. Professional publisher accounted for a third of the journals and 42% of the articles. With the exception of professional and scholar/researcher publishers, most journals were originally subscription journals that made at least their digital version freely available. Arts, humanities and social science journals are largely published by societies and universities outside the major publishing countries. Professional OA publishing is most common in biomedicine, mathematics, the sciences and engineering. Approximately a quarter of the journals are hosted on national/international platforms, in Latin America, Eastern Europe and Asia largely published by universities and societies without the need for publishing fees. This type of collaboration between governments, universities and/or societies may be an effective means of expanding open access publications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 | 0.188 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.036 | 0.076 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".