Women in Intensive Care study: a preliminary assessment of international data on female representation in the ICU physician workforce, leadership and academic positions
Bibliographic record
Abstract
BACKGROUND: Despite increasing female enrolment into medical schools, persistent gender gaps exist in the physician workforce. There are limited published data on female representation in the critical care medicine workforce. METHODS: To obtain a global perspective, societies (n = 84; 79,834 members (40,363 physicians, 39,471 non-physicians)) registered with the World Federation of Societies of Intensive and Critical Care Medicine were surveyed. Longitudinal data on female trainee and specialist positions between 2006-2017 were obtained from Australia and New Zealand. Data regarding leadership and academic faculty representation were also collected from national training bodies and other organisations of critical care medicine. RESULTS: Of the 84 societies, 23 had a registered membership of greater than 500 members. Responses were received from 27 societies (n = 55,996), mainly high-income countries, covering 70.1% of the membership. Amongst the physician workforce, the gender distribution was available from six (22%) participating societies-mean proportion of females 37 ± 11% (range 26-50%). Longitudinal data from Australia and New Zealand between 2006 and 2017 demonstrate rising proportions of female trainees and specialists. Female trainee and specialist numbers increased from 26 to 37% and from 13 to 22% respectively. Globally, female representation in leadership positions was presidencies of critical care organisations (0-41%), representation on critical care medicine boards and councils (8-50%) and faculty representation at symposia (7-34%). Significant gaps in knowledge exist: data from low and middle-income countries, the age distribution and the time taken to enter and complete training. CONCLUSIONS: Despite limited information globally, available data suggest that females are under-represented in training programmes, specialist positions, academic faculty and leadership roles in intensive care. There are significant gaps in data on female participation in the critical care workforce. Further data from intensive care organisations worldwide are required to understand the demographics, challenges and barriers to their professional progress.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".