Ethnicity, Child Sex, and the Likelihood of Marriage in Pregnancy: A Novel Analysis of Gender Inequity
Bibliographic record
Abstract
Objective: We assessed the association between fetal sex and the likelihood of marriage during pregnancy. Methods: We analyzed a cohort of 1,334,911 women who were unmarried at conception and had a live birth between 1990 and 2018 in Quebec, Canada. The exposure was fetal sex, determined by ultrasound. The outcome was marriage during pregnancy. We estimated hazard ratios and 95% confidence intervals (CI) for the association of child sex with the likelihood of marriage during pregnancy according to region of origin. Results: Among women who were unmarried at conception, 13.1% of foreign-born women got married during pregnancy compared with 2.6% of Canadian-born women. Women from the Middle East and North Africa who were pregnant with boys were 1.13 times more likely to marry during pregnancy compared with women who were pregnant with girls (95% CI 1.02–1.26). There was no association among Canadian-born women. Conclusion: Women from some cultural minorities who are pregnant with boys may be more likely to marry during pregnancy in Western settings. Gender inequality may manifest as a preference for sons that influences the likelihood of marriage.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".