Improving gender equity in critical care medicine: a protocol to establish priorities and strategies for implementation
Bibliographic record
Abstract
INTRODUCTION: While the number of women entering medical school now equals or surpasses the number of men, gender equity in medicine has not been achieved. Women continue to be under-represented in leadership roles (eg, deans, medical chairs) and senior faculty positions. In addition, women do not enter medical specialties as often as men, which can have important implications for work environment, reimbursement and the delivery of patient care. Compared with other medical specialties (eg, anaesthesiology, dermatology, etc), critical care medicine is a medical specialty with some of the lowest representation of women. While strategies to improve gender equity in critical care medicine exist in the published literature, efforts to comprehensively synthesise, prioritise and implement solutions have been limited.The objective of this programme of work is to establish priorities for the development and implementation of key strategies to improve the outcomes, well-being and experiences of women in critical care in Canada. METHODS AND ANALYSIS: Three phases encompass this programme of work. In phase I, we will catalogue published strategies focused on improving gender inequity across medical specialties through a scoping review. In phase II, we will conduct a modified Delphi consensus process with decision-makers, physicians and researchers to identify key strategies (identified in phase I and proposed by participants in phase II) for improving gender inequity in the specialty of critical care medicine. Finally, in phase III, we will conduct a 1-day stakeholder meeting that engages participants from phase II to build capacity for the development and implementation of top ranked strategies. Data analyses from this programme of work will be both quantitative and qualitative. ETHICS AND DISSEMINATION: The proposed programme of work is a foundational step towards establishing targeted strategies to improve gender inequity in the medical specialty of critical care medicine. Strategies will be prioritised by stakeholders, mapped to preidentified drivers of gender equity in the specialty and be scalable to institutional needs. A final report of our results including the list of top prioritised strategies and implementation objectives will be disseminated to panel participants, critical care leadership teams and major critical care societies who are partners in this work, around the country to facilitate uptake at the local level.The University of Calgary Conjoint Health Research Ethics Board has approved this study (REB16-0890).
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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 | 0.195 | 0.134 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.055 | 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".