Race and sex diversity in Canadian academic surgical societies
Bibliographic record
Abstract
BACKGROUND: It is vital for national professional surgical societies to embrace diversity, inclusion, and equity. This study examines race and sex diversity in two Canadian surgical societies. METHODS: Websites of the Canadian Society of Cardiac Surgeons (CSCS) and the Canadian Association of General Surgeons (CAGS) and previous programs of their annual meetings were reviewed. Leadership positions, conference speakers, and award winners were categorized by race and sex. RESULTS: White males made up the largest category of Cardiac Surgery meeting speakers (73/142 [51%]), CAGS committee members (89/198 [45%]), CAGS past presidents (38/43 [88%]), and General Surgery meeting speakers (841/1472 [57%]). Of the 17 members that made up the CSCS board of directors and officers, 8 were White males (47%), 5 were BIPOC males (29%), 3 were White females (18%), and 1 was a BIPOC female (6%). Of the 42 members of the CAGS board of directors and advisory committee, 16 were White males (38%), 5 were BIPOC males (12%), 17 were White females (40%), and 4 were BIPOC females (10%). CONCLUSIONS: BIPOC individuals and females are underrepresented in both societies compared to White males. However, in CAGS, improvements in representation can be seen in recent years. It is important that both of these organizations continue to embrace diversity.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".