What would happen if hundreds of social scientists and data scientists worked together on a scientific challenge to improve the lives of disadvantaged children in the United States? The Fragile Families Challenge, an ongoing mass research collaboration that uses “big data” collected as part of Princeton University’s Fragile Families and Child Wellbeing Study, is attempting to answer just that.
The challenge, which was launched earlier this year, asked participants from around the world to use this trove of data — some 54 million data points — to predict six key outcomes: grade point average (academic achievement) of the children; grit of the children; material hardship of the household, which is a measure of extreme poverty; eviction of the families; layoff of the caregiver; and whether the primary caregiver would participate in a job skills program. The challenge received 400 applications from researchers in at least 68 institutions representing at least seven countries, and over 150 teams submitted final predictions to the challenge.
The winners and other interested researchers will gather at Princeton on Nov. 16-17 for the Fragile Families Challenge Scientific Workshop, where they will share their methodology and ideas for future projects that may combine predictive modeling, causal inference and in-depth interviews. These models and their potential applications will be published in scientific journals, both individually and collectively.
Excerpted from a longer article by Pooja Makhijani, Princeton University Office of Communications. To read more, see the full article.
Illustration by Kyle McKernan, Office of Communications