Union Instability and Fertility: An International Perspective
Bibliographic record
Abstract
In this article, we analyse the relationship between union instability and cumulated fertility among ever-partnered women in several regions across Europe and the Americas with different patterns of demographic behaviour in terms of fertility levels, union instability and fertility across partnerships. We hypothesise that the relationship between union dissolution and fertility might be less negative in contexts where repartnering is more prevalent. The analysis is performed on a large dataset of 25 countries, combining information from the Harmonised Histories of the Generation and Gender Programme with our own harmonisation of survey data from three Latin American countries. This allows for the inclusion of countries with differing prevalence of union instability as measured by (a) the proportion of women who separated by age 40, and (b) the proportion who repartnered by age 40. We first examine the prevalence of separation and repartnering during reproductive ages across regions, and we estimate the proportion of cumulated fertility attributable to unions of different ranks using a decomposition method. We then analyse the links between union instability and the number of children born by age 40 among ever-partnered and ever-repartnered women, using Poisson regression. Despite observing a high degree of heterogeneity in the proportions of births occurring in the context of repartnering both within and between regions, we find a pattern where a greater prevalence of repartnering by age 40 is accompanied by higher cumulated fertility in second or subsequent unions. Our multivariate findings reveal a negative statistical relationship between separation and cumulated fertility that is partially offset by repartnering in some contexts, and that the time spent in a union during the reproductive lifespan is a key determinant of cumulated fertility, regardless of national context and independently from age at union formation and union rank.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".