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Record W4296797663 · doi:10.3389/ijph.2022.1604869

Ethnicity, Child Sex, and the Likelihood of Marriage in Pregnancy: A Novel Analysis of Gender Inequity

2022· article· en· W4296797663 on OpenAlexafffundabout
Nathalie Auger, Clara Bolster‐Foucault, Marianne Bilodeau‐Bertrand, Sahar Khademi, Améyo Djeha

Bibliographic record

VenueInternational Journal of Public Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsUniversité de MontréalMcGill University Health CentreInstitut National de Santé Publique du QuébecHealth Canada
FundersFonds de Recherche du Québec - Santé
KeywordsPregnancyMedicineDemographyEthnic groupConfidence intervalHazard ratioPublic healthObstetrics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.103
GPT teacher head0.379
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes3
Has abstractyes

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