Parenthood and neurosurgery in Europe a white paper from the European Association of Neurosurgical Societies’ Diversity in Neurosurgery Committee Part I – Family Planning and Practice during Pregnancy
Bibliographic record
Abstract
Introduction: Family and work have immensely changed and become intertwined over the past half century for both men and women. Additionally, alongside to traditional family structures prevalent, other forms of families such as single parents, LGBTQ + parents, and bonus families are becoming more common. Previous studies have shown that surgical trainees regularly leave residency when considering becoming a parent due to the negative stigma associated with pregnancy during training, dissatisfaction with parental leave options, inadequate lactation and childcare support, and desire for greater mentorship on work-life integration. Indeed, parenthood is one of the factors contributing to attrition in surgical specialities, neurosurgery not being an exception. Research question: The Diversity in Neurosurgery Committee (DC) of the European Association of Neurosurgical Societies (EANS) recognizes the challenges individuals face in parenthood with neurosurgery and wishes to address them in this white paper. Materials and methods: In the following sections, the authors will focus on the issues pertaining to family planning and neurosurgical practice during pregnancy in itemized fashion based on an exhaustive literature search and will make recommendations to address the matters raised. Results: Potential solutions would be to further improve the work-family time ration as well as improving working conditions in the hospital. Discussion and conclusion: While many obstacles have been quoted in the literature pertaining to parenthood in medicine, and in neurosurgery specifically, initiatives can and should be undertaken to ensure not only retention of colleagues, but also to increase productivity and job satisfaction of those seeking to combine neurosurgery and a family life, regardless of their sexual identity and orientation.
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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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".