Twinning Rates in Developed Countries: Trends and Explanations
Why this work is in the frame
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Bibliographic record
Abstract
The twinning rate has increased dramatically over the last four decades in developed countries. Two main factors account for this increase: delayed childbearing, as older women tend to have twins more frequently than younger ones, and the expansion of medically assisted reproduction (MAR), which carries an increased probability of multiple births. Using civil registration data, we estimate the share of the increase in twinning rates attributable to the rise in the age at childbearing and to MAR. The effect of MAR is estimated to be about three times as important as the effect of delayed childbearing. Negative health outcomes associated with multiple births and the cost of MAR have raised concerns. We find that in one‐quarter of developed countries with the relevant data, the twinning rate reached a plateau around the early 2000s and decreased thereafter. We examine the reasons for this reversal, in particular changes in MAR policies and practices.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it