Exclusion of the non-English-speaking world from the scientific literature: Recommendations for change for addiction journals and publishers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: While English is only the native language of 7.3% of the world's population and less than 20% can speak the language, nearly 75% of all scientific publications are English. Aim: To describe how and why scientific contributions from the non-English-speaking world have been excluded from addiction literature, and put forward suggestions for making this literature more accessible to the non-English-speaking population. Methods: A working group of the International Society of Addiction Journal Editors (ISAJE) conducted an iterative review of issues related to scientific publishing from the non-English-speaking world. Findings: We discuss several issues stemming from the predominance of English in the scientific addiction literature, including historical drivers, why this matters, and proposed solutions, focusing on the increased availability of translation services. Conclusion: The addition of non-English-speaking authors, editorial team members, and journals will increase the value, impact, and transparency of research findings and increase the accountability and inclusivity of scientific 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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it