177 International Authorship Trends in Academic Neurosurgery and Effect of Double-Blind Review
Bibliographic record
Abstract
INTRODUCTION: There is a lack of data on international publication rates and whether reviewer biases exist that may affect diversity of authorship. METHODS: Articles published within Neurosurgery, Journal of Neurosurgery (JNS), and World Neurosurgery (WNS) were collected from 2000-2019. Country affiliation data was assigned and analyzed with respect to journal, year of publication, neurosurgical subspeciality, and relative impact. RESULTS: Across 23,325 articles, lead authorship consisted of United States (42.9%, N = 10,005), Japan (9.9%, N = 2,305), China (9.3%, N = 2,167), Germany (5.1%, N = 1,187), South Korea (3.3%, N = 773), Italy (3.3%, N = 773), Canada (3.3%, N = 769), and other nations (22.9%, N = 5,346). Rates of publications did not differ across United States, Asian countries, South/Latin American countries, or African countries pre- and post-initiation of double-blind review in Neurosurgery (p > 0.05). Annual percentage of publications showed highest relative decrease for the United States (-0.48% per year, r 2 = 0.194) and increase for China (0.87% per year, r 2 = 0.761). WNS published fewer articles from the United States compared to Neurosurgery or JNS (Mean difference [MD] -20.6%, p < 0.001), and more articles from Asian (MD +23.5%, p < 0.001), Latin/South American (MD +1.4%, p < 0.001), and African countries (MD +0.8%, p < 0.001). Unbiased co-authorship clustering by country demonstrated that certain countries were more likely to publish together based on geopolitical characteristics. CONCLUSIONS: There is a higher relative contribution to neurosurgery publications from authors in the United States compared to other countries. This effect is not due to potential biases in single-blind review, as evidenced by a natural experiment comparing authorship rates at Neurosurgery pre- and post-initiation of double-blind review in 2011. Additional research is needed to determine whether other biases contribute to differences in publication rates across countries.
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 | 0.461 | 0.758 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.023 | 0.022 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".