Women in cardiovascular imaging: a call for action to address ongoing challenges
Bibliographic record
Abstract
AIMS: The EACVI Scientific Initiatives Committee and the EACVI women's taskforce conducted a global survey to evaluate the barriers faced by women in cardiovascular imaging (WICVi). METHODS AND RESULTS: In a prospective international survey, we assessed the barriers faced at work by WICVi. Three hundred fourteen participants from 53 countries responded. The majority were married (77%) and had children (68%), but most reported no flexibility in their work schedule during their pregnancy or after their maternity leave. More than half of the women reported experiencing unconscious bias (68%), verbal harassment (59%), conscious bias (51%), anxiety (70%), lack of motivation (60%), imposter syndrome (54%), and burnout (61%) at work. Furthermore, one in five respondents had experienced sexual harassment, although this was rarely reported formally. The majority reported availability of mentorship (73%), which was mostly rated as 'good' or 'very good'. While more than two-thirds of respondents (69%) now reported being well trained and qualified to take on leadership roles in their departments, only one-third had been afforded that opportunity. Despite the issues highlighted by this survey, >80% of the participating WICVi would still choose cardiovascular imaging if they could restart their career. CONCLUSION: The survey has highlighted important issues faced by WICVi. While progress has been made in areas such as mentorship and training, other issues including bullying, bias, and sexual harassment are still widely prevalent requiring urgent action by the global cardiovascular imaging community to collectively address and resolve these challenges.
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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 | 0.026 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".