Race and Ethnicity in Otolaryngology Academic Publications
Bibliographic record
Abstract
OBJECTIVE: Within otolaryngology, race is commonly included as a study covariate; however, its value in clinical practice is unclear. This study sought to explore how race and ethnicity have been used and applied over time in otolaryngology publications. DATA SOURCES: PubMed database. REVIEW METHODS: A systematic review was done to identify original otolaryngology studies between January 1, 1946, and June 25, 2020, with the following search terms: "otolaryngology" AND "race" OR "ethnicity." RESULTS: Of the 1984 yielded studies, 932 were included in the final analysis. Only 2 studies (0.2%) defined race, and 172 (18.5%) gave participants the opportunity to self-identify race. Less than half (n = 322, 43.8%) of studies controlled for confounders. One hundred studies (10.7%) linked race to genetic factors. An overall 564 (60.5%) made conclusions about race, and 232 (24.9%) mentioned that race is relevant for clinical decision making. The majority of studies had first and senior authors from high-income countries (93.9% and 93.8%, respectively). Over time, there was a significant increase in publications that controlled for confounders, the number of race categories used, and studies that highlighted disparities. CONCLUSION: Race and ethnicity are often poorly defined in otolaryngology publications. Furthermore, publications do not always control for confounding variables or allow participants to self-identify race. On the basis of our findings, we suggest 7 foundational principles that can be used to promote equitable research in otolaryngology publications. Future efforts should focus on incorporating research guidelines for race and ethnicity into journal publication standards.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".