A multi-faceted approach to sex and gender equity in solid organ transplantation: The Women in Transplantation Initiative of The Transplantation Society
Bibliographic record
Abstract
The advancement of women's careers in transplantation continues to be challenging. Academic careers in both basic and clinical disciplines in transplantation, such as surgery and management of end organ failure in medical specialties, have been underrepresented by diverse genders and ethnicities. Over the last decade, the Women in Transplantation Initiative (WIT) has solidified to becoming an internationally recognized organization with activities focused on diversity and inclusion in terms of the sexes. The WIT organization is divided into 3 pillars that address career advancement and networking (Pillar 1), scientific investigation and presentations on sex and gender in transplantation (Pillar 2) and investigating and facilitating equitable access to transplantation for women throughout the world (Pillar 3). By taking this multipronged approach of collaborating across continents, leveraging virtual platforms for information dissemination and discussion, and providing financial support for research, WIT has become a highly visible grass roots organization that aims to improve the experience of women as transplant professionals as well as transplant donors and recipients.
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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 | 0.040 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.019 | 0.020 |
| Scholarly communication | 0.019 | 0.009 |
| Open science | 0.002 | 0.028 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 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".