P1-242 Impact of work place policies and educational attainment on women's childbearing decisions in Canada
Bibliographic record
Abstract
Under Canada's Employment Insurance (EI) system, parents are entitled to receive up to 50 weeks of parental leave at 55% of salary to a maximum of $413/week. In addition, many companies “top-up” these EI benefits so parents receive their full salary during parental leave. Despite this national policy, women with higher education are more likely to delay childbearing. Women who delay childbearing, particularly past age 35, are at increased risk of infertility, pregnancy and birth complications. This analysis aimed to assess whether workplace support impacted women's decisions regarding when to have their first baby and how educational attainment affected this relationship. Within 3 months of delivery, women who had given birth to their first live-born infant in 2002/2003 within two large urban regions in Alberta, Canada, were randomly selected to participate in a telephone survey. Logistic regression was used to assess the relationship between workplace support, educational attainment and timing of first pregnancy. Among 836 women with a planned pregnancy, 26% agreed that the support or lack of support for pregnant women at their workplace affected their decision about when to begin their family. After controlling for age and income, women who had completed a post-graduate degree were three times (OR=3.39, 95% CI 1.69 to 6.81) more likely to indicate that the support or lack of support for pregnant women in the workplace affected their childbearing decisions. In spite of national policies, and the potential risks associated with delayed childbearing, workplace support impacts timing of pregnancy, particularly for highly educated women.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".