Analysis of gender gap in North American radiation oncology society committees
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Achieving gender equity in medicine remains elusive. We evaluated the gender distribution within executive roles of North American radiation oncology societies and assessed the relationship between gender, committee rank, academic rank and research productivity. METHODS: 205 committee members were identified from four radiation oncology society webpages. Members were categorised into leadership positions and academic ranks. For each, the Hirsch index (h-index), m-index, publications, citations and years of research were extracted from the Scopus database. This study complies with Sex and Gender Equity in Research (SAGER) guidelines for observational studies. RESULTS: Radiation oncology committees were comprised of significantly more men (72.7%, p<0.0001). Within these committees, men significantly outnumbered women in leadership positions, holding 73.5% of positions (p<0.0001). This trend extended to academic ranks and research productivity, with men occupying 72.7% of positions (p<0.001) and having greater mean (±SE of the mean) research productivity with more publications (171.1±12.9 vs 97.3±18.7, p<0.0001), citations (7785±785.1 vs 44061±1168, p=0.0002), h-index (36.17±2.2 vs 22.9±3.6, p=0.0002) and years of research (29.8±1.2 vs 16.7±1.7, p<0.0001). The m-index showed no significant gender difference among men and women (1.2±0.06 vs 1.2±0.09, p>0.05). CONCLUSION: While men occupy more leadership roles and show higher research productivity as measured by the h-index, accounting for years of active research with the m-index showed no significant difference between genders. This underscores the need for targeted strategies such as mentorship programmes and gender-equity policies to promote greater representation of women in the discipline.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it