Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the growth and changes in Bioline International (BI), a non‐profit scholarly publications aggregator, distributor, publisher, and publishing assistance service founded in 1993 and operated by scientists and librarians who have a strong commitment to the principles of open access (OA) and to broad distribution, by electronic means, of scientific information. Design/methodology/approach The paper presents a case study of BI. Findings BI has changed considerably since its early days. Initially, it largely consisted of e‐mailed versions of printed peer‐reviewed scientific journals from developing countries; these versions were generally e‐mailed as ASCII text and could lack figures and graphics. But much has changed, both due to technological capabilities and due to policy changes. BI has increasingly moved toward inclusion of e‐only journals, and has itself tried its hand at publishing a small selection of highly specialized, fully online journals, with OA portions. In January 2004, it converted its entire web site to OA (formerly, some portions were restricted). It has been enabled to become a pure OA provider of scholarly information through a model of grant support and partnerships with other institutions, including many international institutes and foundations and the University of Toronto. Originality/value BI success is provides an unusual and successful model for strong support for OA to scholarly research and scientific information, especially from developing countries. It also provides a model of flexibility and adaptability, with minimal resources, and demonstrates the possibilities which emerge from truly broad‐based collaborations, across multiple countries, and between large and small societies, academe, and non‐governmental organizations.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.432 | 0.285 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".