Nicolás Soler, Tom Emery, Agnieszka Kanas
Sociological Science June 2, 2026
10.15195/v13.a23
Abstract
How first-time parents arrange childcare has critical implications for their careers and the child’s development. Previous research shows that childcare choices are shaped by family care availability, understood as an additive function of a small set of parental and grandparental characteristics. However, research on family networks suggests that care availability is rather a non-linear, non-additive function of large family networks. We compare the predictive ability of these two perspectives using a machine learning framework and register-based family network data. We find that considering how the child’s great-grandparents, aunts, uncles, and cousins shape care availability, and modeling their influence using more flexible models, provides small yet significant improvements in predictive ability, particularly among more disadvantaged parents. Predictions are driven by parents’ and grandparents’ socioeconomic characteristics, but cousins’ age and daycare use are important yet understudied predictors. Other important understudied predictors include parents’ self-employment, healthcare spending, and timing of daycare uptake.
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Reproducibility Package: Code to reproduce the results can be found at https://doi.org/10.5281/zenodo.19189668. The data are non-public microdata from Statistics Netherlands that are accessible to accredited researchers under certain conditions (see Statistics Netherlands 2026).
- Citation: Soler, Nicolás, Tom Emery, Agnieszka Kanas, 2026. “Family Networks and Childcare Choices: A Predictive Machine Learning Approach” Sociological Science 13: 589-613.
- Received: February 18, 2026
- Accepted: March 23, 2026
- Editors: Stephen Vaisey, Michael Rosenfeld
- DOI: 10.15195/v13.a23







Original article:
Status Ambiguity and Multiplicity in the Selection of NBA Awards
Comment:
There Is Cumulative Status Bias and Status Entrenchment in NBA Awards: Comment on McMahan and Shor (2024)