Lost in translation: the challenges of global communication in medical education publishing
Bibliographic record
Abstract
CONTEXT: An academic journal serves its purpose by being read and understood. International medical education journals that want to reach a wider readership must be accessible to a multitude of cultures and contexts. It is therefore important that authors and editors consider how their use of language will be interpreted by health care education colleagues who work in different settings. Given the increasing importance of communicating research findings in health care education, it is surprising that no surveys of the comprehensibility of medical education publications have been published in the medical education literature. METHODS: We (a group of education researchers from Europe and North America) set out to examine the comprehensibility of a defined set of recently published medical education papers. We surveyed all the articles published in four major international journals on medical education during the first 5 months of 2008 and searched for terminology that might prove obscure or confusing to an international readership. RESULTS: We found that many of the articles surveyed included terminology, contextual descriptions, acronyms and titles that assumed a shared understanding of setting between authors and readers. We include illustrative examples in the text. DISCUSSION: Terminological and contextual challenges for international readers are common features of the research publications surveyed. In order that the findings of education research may be more widely disseminated and understood, it is important that authors, referees and editors pay attention to the comprehensibility of the language they use in articles selected for publication.
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 | 0.176 | 0.428 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.011 | 0.033 |
| Scholarly communication | 0.050 | 0.050 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".