Tag Archives | Kinship

Family Networks and Childcare Choices: A Predictive Machine Learning Approach

Nicolás Soler, Tom Emery, Agnieszka Kanas

Sociological Science June 2, 2026
10.15195/v13.a23


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.

Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.


Nicolás Soler: Department of Public Administration and Sociology, Erasmus University Rotterdam.
E-mail: soleralvarezmiranda@essb.eur.nl.

Tom Emery: Department of Public Administration and Sociology, Erasmus University Rotterdam.
E-mail: tom@odissei-data.nl.

Agnieszka Kanas: Department of Public Administration and Sociology, Erasmus University Rotterdam.
E-mail: kanas@essb.eur.nl.


Supplemental Materials

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


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Evolutionary Influences on Assistance to Kin: Evidence from the Panel Study of Income Dynamics

Andrew J. Cherlin

Sociological Science December 16, 2023
10.15195/v10.a34


Amid the changes that have diversified family life, studies have shown the continuing importance of attachment to kin through established patterns such as ties among full siblings and newer patterns such as efforts by donor-conceived individuals to find their donor siblings. Sociologists have good explanations for the diversity of family forms but not for the persistence of kinship ties. This article argues that evolutionary processes focused on genetic relatedness can provide a partial explanation for both the persistence and expansion of kinship ties. It proposes that the easing of social constraints on family-related behaviors and the resulting expansion of choices may have increased the importance of genetic relatedness in producing the current patterns. To illustrate this perspective, this article examines the consistency between patterns of financial assistance to kin and Hamilton’s rule, derived from the evolutionary theory of inclusive fitness, using the 1985 to 2019 waves of the Panel Study of Income Dynamics (PSID).
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Andrew J. Cherlin: Department of Sociology, Johns Hopkins University
E-mail: cherlin@jhu.edu

Acknowledgements: I thank Dalton Conley, Frank Furstenberg, Rosemary Hopcroft, and Robert Schoen for comments on previous drafts. Data and analysis files are available at the Interuniversity Consortium for Political and Social Research, project number is openicpsr-193132.

  • Citation: Cherlin, Andrew J. 2023. “Evolutionary Influences on Assistance to Kin: Evidence from the Panel Study of Income Dynamics.” Sociological Science 10: 964-988.
  • Received: June 21, 2023
  • Accepted: August 10, 2023
  • Editors: Arnout van de Rijt, Werner Raub
  • DOI: 10.15195/v10.a34


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