Abstract 18955: Post Webinar Survey Responses Regarding Maternity and Legal Rights for Cardiologists
Bibliographic record
Abstract
Introduction/Background: Women are under-represented in cardiology and cardiology subspecialties. Work life challenges are often a stated reason why women do not choose cardiology. Pregnancy and motherhood represent a time of significant challenges to women in cardiology due to lack of support and discrimination. The American Heart Association (AHA)Women in Cardiology (WIC) Committee recently held a case-based webinar to increase awareness about the issues, discuss available resources for support, and understand laws protecting women against discrimination. Goals/Aims: The goal of the survey was to understand the current landscape of perceived institutional support during the maternity period and gauge awareness of the laws protecting women against discrimination. Methods/Approach: After the webinar, an email survey was sent to all those who registered on behalf of the AHAWIC Committee within 7days of the event. Results/Data: There were 189registrants for the webinar, of which 29(15%)responded to the survey. Of those who responded, 72%were female, 48%were <40years of age, 33%of the attendees were mothers, and 20%reported fertility issues. Almost all respondents reported working in a hospital-based practice (90%),59%were attending physicians and 38%were trainees. Only 28%reported that their work environment was very supportive of mothers and only 31%were aware of maternal legal rights in the workplace. After the webinar, 76%planned to learn or implement new maternal rights related policies in their workplace (Figure 1). Conclusions: Pregnancy and motherhood represent a challenging time in the career of a female cardiologist or trainee. Perceived support in the workplace is low. Very few women know their legal rights, but a majority had a plan to learn more after the webinar. This survey highlights opportunities for the cardiology community and national societies to help support women cardiologists.
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 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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.013 |
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".