Union formation, within‐couple dynamics, and child well‐being: A global macrolevel perspective
Bibliographic record
Abstract
Abstract Studies on global changes in families have greatly increased over the past decade, adopting both a country‐specific and, more recently, a cross‐national comparative perspective. While most studies are focused on the drivers of global changes in families, little comparative research has explored the implications of family processes for the health and well‐being of children. This study aims to fill this gap and launch a new research agenda exploring the intergenerational implications of union‐formation and within‐couple dynamics for children's health and well‐being across low‐ and middle‐income countries (LMICs), both globally, regionally, and by the stage of fertility transition. We do so by adopting a macrolevel perspective and a multi‐axis conceptualization of children's outcomes—health at birth, health in later life, and schooling—and leveraging Demographic and Health Survey and World Bank data across 75 LMICs. Our results show that in societies where partnerships are characterized by more equal status between spouses—that is, where the age range between spouses and differences in years of schooling between partners are narrower—children fare better on several outcomes. These associations are particularly strong in mid‐ and high‐fertility settings. Despite a series of regularities, our results also highlight a set of findings whereby, at a macrolevel, the prevalence of marriage and divorce/separation are not invariably associated with children's outcomes, especially in LMICs where fertility is comparatively lower. We document little cross‐regional heterogeneity, primarily highlighting the centrality of demographic factors such as age vis‐à‐vis, for instance, region‐specific characteristics that are more tied to the social fabric of specific societies.
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 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 | 0.001 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".