Persistent ethnic disparities in authorship within top European and North American medical journals: a serial cross-sectional analysis
Bibliographic record
Abstract
OBJECTIVES: We examined the ethnic origin of authors who published research articles in leading medical journals over the past 2 decades. STUDY DESIGN AND SETTING: We carried out a serial cross-sectional analysis of first and last authors who published original research articles in the British Medical Journal, Lancet, Journal of the American Medical Association, and New England Journal of Medicine in 2002, 2012, and 2022. The main outcome was the change in proportion of authors over time according to ethnic origin (Anglo, North/West European, South/West European, Asian, Arab and Middle Eastern, African), gender (male, female), and institutional affiliation in percentage points. RESULTS: Most authors were of Anglo descent (44%), although the proportion of non-European authors grew between 2002 and 2022. East Asian, South Asian, and Arab and Middle Eastern last authors accounted for a greater proportion of authors over time, gaining between 3 and 6 percentage points, while African authors made no gains. Gains were gender-specific, with non-European men gaining 8 points as first and last authors, but non-European women gaining 5 points as last authors only. Most non-European authors were affiliated with North American (42.9%) or European (22.4%) institutions, while non-European authors from other institutions did not make meaningful gains over time. CONCLUSION: Ethnic diversity of authors in leading medical journals has increased somewhat over time, but non-European men account for most of the gains. Non-European women have yet to make comparable advancement as authors.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchResearch integrity Domain: Incentives · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | MetaresearchResearch integrityScholarly communication Domain: Incentives · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.128 | 0.091 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".