An Eye on Childbearing, Fertility, and Lactation Experiences: A Survey of Canadian Ophthalmologists and Trainees
Bibliographic record
Abstract
• Women in ophthalmology more than men perceived that residency training and clinical practice influenced the number of children they chose to have and their ability to conceive. • Compared to male surgeons, women were more likely to have concerns about future fertility and parental leave. • There were several significant factors which affected parental leave including pressure from colleagues and difficulty finding coverage for clinical practice. • Childbearing and parental leave also negatively influenced ascension to leadership and career advancement in women more than men. • Safe and dedicated spaces for lactation are lacking in the workplace for ophthalmologists, making it challenging to meet breastfeeding goals. To synthesize the experiences of childbearing, fertility, and lactation among Canadian ophthalmologists and trainees. Online, cross-sectional survey. A survey was distributed to Canadian ophthalmologists and trainees between April and August 2022. Likert-type scales were used to measure respondents' agreement with each survey item. Fisher's exact test was used to identify significant differences based on gender. Data were obtained from a total of 137 survey respondents (46% females). Women more than men reported that training and clinical practice influenced the number of children they chose to have (p = 0.002), as well as their ability to conceive (p < 0.001). Compared to their male counterparts, more women had concerns about future fertility (p = 0.040) and parental leave (p = 0.037). Among factors affecting parental leave, pressure from colleagues (p = 0.046) and difficulty finding coverage for clinical practice (p = 0.022) were statistically significant among women more than men. More women reported taking parental leave during medical school, residency, and clinical practice than men (p < 0.001). Childbearing (p = 0.005) and parental leave (p = 0.031) influenced pursuit of leadership roles and opportunities for career advancement among women more than men. Of those with lactation experiences, one-third of women felt they did not have adequate space or storage to facilitate their breastfeeding goals in the workplace. Over the span of their careers, female ophthalmologists and trainees face unparalleled challenges related to childbearing and parenthood duties, coping with infertility and obstetric risks, stigma, inadequate parental leaves, and poor supports for lactation and childcare, while balancing their career demands and aspirations. Garnering an understanding of gender inequities is essential to promote work-family integration within the surgical culture and address the systemic and structural barriers which impose a glass ceiling for female surgeons.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".