Gender differences in publication rates at Canadian Society of Otolaryngology–Head and Neck Surgery annual meetings: An 11-year analysis
Bibliographic record
Abstract
BACKGROUND: Evaluating gender differences in publication rates after conference presentations is an avenue to assess women's contributions to academic medicine. The objective of this study was to assess gender differences in publication rates, time to publication, and subspeciality of publication of abstracts presented at Canadian otolaryngology conferences over an 11-year period. METHODS: Cross-sectional data was obtained from online conference schedules of annual Canadian Society of Otolaryngology-Head and Neck Surgery national meetings between 2009 and 2020. A total of 2111 abstract titles were searched in MedLine via PubMed. Gender of the first and senior author, publication status of presented work, and subspeciality of publication were extracted. RESULTS: Of 2111 scientific abstracts presented between 2009 and 2020, female first and senior authors accounted for 29.0% and 12.8% of published abstracts, respectively. There was a significant difference in the publication rate of senior authors by gender (p < 0.01). Male senior authors had a 9.70% higher rate of publication compared to female senior authors. Posters with a female first author were 33.0% (OR: 0.67; 95% CI 0.49-0.91) less likely to be published compared to posters with a male first author. Similarly, posters with a female senior author were 34.0% (OR: 0.66; 95% CI 0.45-0.96) less likely to be published. There was a significant difference in discipline of publication by gender of the senior author (p < 0.001). Male senior authors were more likely to supervise projects in otology while female senior authors were more likely to supervise projects in education and pediatrics. The time to publication and impact factor of the journal of publication did not differ by gender. CONCLUSION: Gender disparities exist in the publication rates of first and senior authors at Canadian otolaryngology meetings. Female senior authors have significantly lower publication rates compared to their male colleagues and differences exist in publication rates after poster presentations. Investigation of gender gaps in academic medicine, research productivity, and publications is essential for development of a diverse, equitable, and inclusive workforce in otolaryngology.
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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 | 0.024 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.017 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".