Diversity in health professional education scholarship: a document analysis of international author representation in leading journals
Bibliographic record
Abstract
OBJECTIVES: The global distribution of health professionals and associated training programmes is wide but prior study has demonstrated reported scholarship of teaching and learning arises from predominantly Western perspectives. DESIGN: We conducted a document analysis to examine authorship of recent publications to explore current international representation. DATA SOURCES: The table of contents of seven high-impact English-language health professional education journals between 2008 and 2018 was extracted from Embase. ELIGIBILITY CRITERIA: The journals were selected according to highest aggregate ranking across specific scientific impact indices and stating health professional education in scope; only original research and review articles from these publications were included for analysis. DATA EXTRACTION AND SYNTHESIS: The table of contents was extracted and eligible publications screened by independent reviewers who further characterised the geographic affiliations of the publishing research teams and study settings (if applicable). RESULTS: A total 12 018 titles were screened and 7793 (64.8%) articles included. Most were collaborations (7048, 90.4%) conducted by authors from single geographic regions (5851, 86%). Single-region teams were most often formed from countries in North America (56%), Northern Europe (14%) or Western Europe (10%). Overall lead authorship from Asian, African or South American regions was less than 15%, 5% and 1%, respectively. Geographic representation varied somewhat by journal, but not across time. CONCLUSIONS: Diversity in health professional education scholarship, as marked by nation of authors' professional affiliations, remains low. Under-representation of published research outside Global North regions limits dissemination of novel ideas resulting in unidirectional flow of experiences and a concentrated worldview of teaching and learning.
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 | 0.077 | 0.228 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.086 | 0.095 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".