Premarital Pregnancy in China: Cohort Trends and Educational Gradients
Bibliographic record
Abstract
In China, premarital sexual and reproductive behavior is seldom considered and poorly understood. Increases in premarital pregnancy are thought to not only illuminate a decoupling of marriage and sexual/reproductive behavior but also serve as a key feature of family change in East Asia. This study assesses change across cohorts in the likelihood of premarital pregnancy and the extent to which change differs by educational attainment. Drawing on the 2017 China Fertility Survey, we apply a discrete-time, competing-risk survival analysis to a nationally representative sample of 221,990 women born between 1960 and 1999. Women born in the 1980s and 1990s are more likely than those born in the 1960s and 1970s to experience a pregnancy prior to first marriage. This cohort trend is driven by increases in premarital pregnancy among women with a high school education or less. The less educated women and their college counterparts increasingly diverge in the likelihood of experiencing a premarital pregnancy. The diverging patterns of premarital pregnancy underscore the urgency to shift the focus of China's family planning programs from fertility control to reproductive health, with an emphasis on providing information and services to disadvantaged unmarried individuals.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".