PreFer

Data challenge for Predicting Fertility outcomes in the Netherlands

Image credits: https://stulp.gmw.rug.nl/prefer/

We participate in the PreFer challenge to understand how predictable fertility decisions in the Netherlands are. This will advance our understanding of fertility.

Why predict fertility outcomes in a data challenge?

Quoting the website challenge,

Fertility is widely studied in diverse disciplines due to its importance to individuals and societies. A lot of factors have been identified that are related to fertility outcomes. Yet these important factors only explain a fraction of the variation in fertility outcomes and we are unable to explain even their short-term changes. What do we miss?

This data challenge can potentially advance our understanding of fertility behavior and improve social policies and family planning in several ways. Measuring how well different factors and models can predict fertility outcomes for new cases will show which factors are more important. It can narrow down a scope for potential interventions and help people reach their desired family size. Comparing and interpreting different models submitted to a data challenge (e.g. theory- and data-driven) can identify new factors currently overlooked by the theories of fertility and highlight the gaps in current knowledge (e.g. important interactions or non-linear effects)

Participating organisations

University of Groningen
Princeton University
ODISSEI
Netherlands eScience Center
Social Sciences & Humanities
Social Sciences & Humanities

Team

Malte Lüken
Malte Lüken
Lead RSE
Netherlands eScience Center
Flavio Hafner
Flavio Hafner
eScience Research Software Engineer
Netherlands eScience Center

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